From 0443820ba1561d48359d5c174abd28ab5a6a7150 Mon Sep 17 00:00:00 2001 From: Samuel Monson Date: Wed, 1 Oct 2025 15:27:48 -0400 Subject: [PATCH 01/10] Add basic prefix column Signed-off-by: Samuel Monson --- src/guidellm/data/objects.py | 2 ++ src/guidellm/data/utils.py | 5 +++++ 2 files changed, 7 insertions(+) diff --git a/src/guidellm/data/objects.py b/src/guidellm/data/objects.py index 04c5407d..b4a38719 100644 --- a/src/guidellm/data/objects.py +++ b/src/guidellm/data/objects.py @@ -31,6 +31,7 @@ GenerativeDatasetColumnType = Literal[ "prompt_tokens_count_column", "output_tokens_count_column", + "prefix_column", "text_column", "image_column", "video_column", @@ -195,6 +196,7 @@ class GenerativeDatasetArgs(StandardBaseDict): split: str | None = None prompt_tokens_count_column: str | None = None output_tokens_count_column: str | None = None + prefix_column: str | None = None text_column: str | list[str] | None = None image_column: str | list[str] | None = None video_column: str | list[str] | None = None diff --git a/src/guidellm/data/utils.py b/src/guidellm/data/utils.py index 7d53a054..d2fa1f9c 100644 --- a/src/guidellm/data/utils.py +++ b/src/guidellm/data/utils.py @@ -80,6 +80,11 @@ DEFAULT_COLUMN_NAMES: dict[str, list[str]] = { "prompt_tokens_count": ["prompt_tokens_count", "input_tokens_count"], "output_tokens_count": ["output_tokens_count", "completion_tokens_count"], + "prefix_column": [ + "system_prompt", + "system", + "prefix", + ], "text_column": [ "prompt", "instruction", From 7f3960b809ed2ca750f410957d44525188f3e37d Mon Sep 17 00:00:00 2001 From: Samuel Monson Date: Wed, 1 Oct 2025 15:55:18 -0400 Subject: [PATCH 02/10] Add basic prefix support back to synthetic data Signed-off-by: Samuel Monson --- src/guidellm/data/deserializers/synthetic.py | 21 +++++++++++++++++--- 1 file changed, 18 insertions(+), 3 deletions(-) diff --git a/src/guidellm/data/deserializers/synthetic.py b/src/guidellm/data/deserializers/synthetic.py index 2335596d..d4287aea 100644 --- a/src/guidellm/data/deserializers/synthetic.py +++ b/src/guidellm/data/deserializers/synthetic.py @@ -25,6 +25,11 @@ class SyntheticTextDatasetConfig(StandardBaseModel): + prefix_tokens: int = Field( + description="The number of shared prefix tokens to prepend to each prompt.", + ge=0, + default=0, + ) prompt_tokens: int = Field( description="The average number of text tokens generated for prompts.", gt=0, @@ -104,20 +109,29 @@ def __iter__(self) -> Iterator[dict[str, Any]]: ) ) + # Create a shared prefix if specified + if self.config.prefix_tokens > 0: + prefix = self._create_prompt(self.config.prefix_tokens, faker) + else: + prefix = "" # Always have a prefix key for consistency + while True: prompt_tokens_count = next(prompt_tokens_sampler) output_tokens_count = next(output_tokens_sampler) yield { + "prefix": prefix, "prompt": self._create_prompt( - prompt_tokens_count, samples_generated, faker + prompt_tokens_count, faker, f"{samples_generated} " ), "prompt_tokens_count": prompt_tokens_count, "output_tokens_count": output_tokens_count, } samples_generated += 1 - def _create_prompt(self, prompt_tokens_count: int, index: int, faker: Faker) -> str: + def _create_prompt( + self, prompt_tokens_count: int, faker: Faker, unique: str = "" + ) -> str: prompt_token_ids = [] avg_chars_per_token = 5 margin_of_safety = 1.5 @@ -128,7 +142,7 @@ def _create_prompt(self, prompt_tokens_count: int, index: int, faker: Faker) -> num_chars = ( prompt_tokens_count * avg_chars_per_token * margin_of_safety * attempts ) - text = f"{index} " + faker.text(max_nb_chars=num_chars) + text = unique + faker.text(max_nb_chars=num_chars) prompt_token_ids = self.processor.encode(text) return self.processor.decode( @@ -166,6 +180,7 @@ def __call__( ), features=Features( { + "prefix": Value("string"), "prompt": Value("string"), "prompt_tokens_count": Value("int32"), "output_tokens_count": Value("int32"), From 37c932d80d77e05375453e5a9247c6b925908896 Mon Sep 17 00:00:00 2001 From: Samuel Monson Date: Wed, 1 Oct 2025 15:40:30 -0400 Subject: [PATCH 03/10] Update templates to support prefix_column Signed-off-by: Samuel Monson --- src/guidellm/data/formatters/templates.py | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/src/guidellm/data/formatters/templates.py b/src/guidellm/data/formatters/templates.py index 2cf6e2f3..52db73b1 100644 --- a/src/guidellm/data/formatters/templates.py +++ b/src/guidellm/data/formatters/templates.py @@ -22,11 +22,7 @@ class JinjaTemplatesRegistry(RegistryMixin[Union[Template, str]]): textwrap.dedent(""" {% set obj = { "json_body": { - "prompt": ( - text_column[0] - if text_column and text_column|length == 1 - else text_column - ) + "prompt": prefix_column[0]|default("") + text_column[0] } } %} @@ -52,6 +48,10 @@ class JinjaTemplatesRegistry(RegistryMixin[Union[Template, str]]): {% set obj = { "json_body": { "messages": [ + { + "role": "system", + "content": prefix_column[0]|default("") + }, { "role": "user", "content": [] @@ -61,11 +61,11 @@ class JinjaTemplatesRegistry(RegistryMixin[Union[Template, str]]): } %} {%- for item in text_column or [] %} - {% do obj["json_body"].messages[0].content.append({"type": "text", "text": item}) %} + {% do obj["json_body"].messages[1].content.append({"type": "text", "text": item}) %} {%- endfor %} {%- for item in image_column or [] %} - {% do obj["json_body"].messages[0].content.append({ + {% do obj["json_body"].messages[1].content.append({ "type": "image_url", "image_url": encode_image( item, @@ -78,7 +78,7 @@ class JinjaTemplatesRegistry(RegistryMixin[Union[Template, str]]): {%- endfor %} {%- for item in video_column or [] %} - {% do obj["json_body"].messages[0].content.append({ + {% do obj["json_body"].messages[1].content.append({ "type": "video_url", "video_url": encode_video( item, From a635030a518e9b7697ec35e372fb1fcb61e21578 Mon Sep 17 00:00:00 2001 From: Samuel Monson Date: Thu, 2 Oct 2025 12:24:01 -0400 Subject: [PATCH 04/10] Add librosa and torch to pyproject Signed-off-by: Samuel Monson --- pylock.toml | 2465 ++++++++++++++++++++++++++---------------------- pyproject.toml | 9 + 2 files changed, 1340 insertions(+), 1134 deletions(-) diff --git a/pylock.toml b/pylock.toml index 2fa1b28e..4c6468c2 100644 --- a/pylock.toml +++ b/pylock.toml @@ -3,8 +3,8 @@ lock-version = "1.0" requires-python = "<4.0,>=3.9.0" environments = [ - "python_version ~= \"3.10\"", - "python_version < \"3.10\" and python_version >= \"3.9\"", + "python_version ~= \"3.12\"", + "python_version < \"3.12\" and python_version >= \"3.9\"", ] extras = ["dev", "recommended"] dependency-groups = ["default"] @@ -44,6 +44,24 @@ dependencies = [ "tomli>=2.0.1; python_version < \"3.11\"", ] +[[packages]] +name = "blobfile" +version = "3.1.0" +requires-python = ">=3.8.0" +sdist = {name = "blobfile-3.1.0.tar.gz", url = 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a/pyproject.toml +++ b/pyproject.toml @@ -13,6 +13,13 @@ include = ["*"] [tool.pdm] distribution = true +[[tool.pdm.source]] +name = "torch" +type = "find_links" +#url = "https://download.pytorch.org/whl/cpu/torch_stable.html" +url = "https://download.pytorch.org/whl/cpu/torch/" +include_packages = ["torch"] + # ************************************************ # ********** Project Metadata ********** @@ -64,6 +71,8 @@ dependencies = [ "sanic", "transformers", "uvloop>=0.18", + "librosa>=0.11.0", + "torch>=2.8.0", ] [project.optional-dependencies] From 81ee731a3bb1d38ff146bfbe844eeb978f65cdca Mon Sep 17 00:00:00 2001 From: Samuel Monson Date: Thu, 2 Oct 2025 12:26:10 -0400 Subject: [PATCH 05/10] Reimplement advanced prefix control Signed-off-by: Samuel Monson --- src/guidellm/data/deserializers/__init__.py | 2 + src/guidellm/data/deserializers/synthetic.py | 73 +++++++++++++++++--- 2 files changed, 67 insertions(+), 8 deletions(-) diff --git a/src/guidellm/data/deserializers/__init__.py b/src/guidellm/data/deserializers/__init__.py index fdee12ce..1062f2b7 100644 --- a/src/guidellm/data/deserializers/__init__.py +++ b/src/guidellm/data/deserializers/__init__.py @@ -25,6 +25,7 @@ SyntheticTextDatasetConfig, SyntheticTextDatasetDeserializer, SyntheticTextGenerator, + SyntheticTextPrefixBucketConfig, ) __all__ = [ @@ -46,6 +47,7 @@ "SyntheticTextDatasetConfig", "SyntheticTextDatasetDeserializer", "SyntheticTextGenerator", + "SyntheticTextPrefixBucketConfig", "TarFileDatasetDeserializer", "TextFileDatasetDeserializer", ] diff --git a/src/guidellm/data/deserializers/synthetic.py b/src/guidellm/data/deserializers/synthetic.py index d4287aea..bfd61e7d 100644 --- a/src/guidellm/data/deserializers/synthetic.py +++ b/src/guidellm/data/deserializers/synthetic.py @@ -1,8 +1,10 @@ from __future__ import annotations from collections.abc import Iterator +from math import gcd from pathlib import Path -from typing import Any, Callable +from random import Random +from typing import Any, Callable, ClassVar import yaml from datasets import Features, IterableDataset, Value @@ -21,15 +23,33 @@ "SyntheticTextDatasetConfig", "SyntheticTextDatasetDeserializer", "SyntheticTextGenerator", + "SyntheticTextPrefixBucketConfig", ] -class SyntheticTextDatasetConfig(StandardBaseModel): +class SyntheticTextPrefixBucketConfig(StandardBaseModel): + bucket_weight: int = Field( + description="Weight of this bucket in the overall distribution.", + gt=0, + default=100, + ) + prefix_count: int = Field( + description="The number of unique prefixs to generate for this bucket.", + ge=1, + default=1, + ) prefix_tokens: int = Field( - description="The number of shared prefix tokens to prepend to each prompt.", + description="The number of prefix tokens per-prompt for this bucket.", ge=0, default=0, ) + + +class SyntheticTextDatasetConfig(StandardBaseModel): + prefix_buckets: list[SyntheticTextPrefixBucketConfig] | None = Field( + description="Buckets for the prefix tokens distribution.", + default=None, + ) prompt_tokens: int = Field( description="The average number of text tokens generated for prompts.", gt=0, @@ -75,6 +95,8 @@ class SyntheticTextDatasetConfig(StandardBaseModel): class SyntheticTextGenerator: + PREFIX_DISTRIBUTION_PRECISION: ClassVar[int] = 1000 + def __init__( self, config: SyntheticTextDatasetConfig, @@ -110,17 +132,15 @@ def __iter__(self) -> Iterator[dict[str, Any]]: ) # Create a shared prefix if specified - if self.config.prefix_tokens > 0: - prefix = self._create_prompt(self.config.prefix_tokens, faker) - else: - prefix = "" # Always have a prefix key for consistency + rand = Random(self.random_seed + 3) + prefix_iter = self._create_prefix_iter(faker, rand) while True: prompt_tokens_count = next(prompt_tokens_sampler) output_tokens_count = next(output_tokens_sampler) yield { - "prefix": prefix, + "prefix": next(prefix_iter), "prompt": self._create_prompt( prompt_tokens_count, faker, f"{samples_generated} " ), @@ -149,6 +169,43 @@ def _create_prompt( prompt_token_ids[:prompt_tokens_count], skip_special_tokens=True ) + def _create_prefix_iter(self, faker: Faker, rand: Random) -> Iterator[str]: + if not self.config.prefix_buckets: + while True: + yield "" + + total_weight = sum( + bucket.bucket_weight for bucket in self.config.prefix_buckets + ) + if total_weight <= 0: + raise ValueError("Total weight of prefix buckets must be greater than 0.") + + # Calculate the divisor needed to achieve the minimum + # number of prompts given the weight ratios + percents = [ + int( + self.PREFIX_DISTRIBUTION_PRECISION + * bucket.bucket_weight + / bucket.prefix_count + / total_weight + ) + for bucket in self.config.prefix_buckets + ] + common_divisor = gcd(*percents) + + # Create prefix list maintaining the correct distribution + prefixes = [] + for bucket, percent in zip(self.config.prefix_buckets, percents): + bucket_prefixes = [ + self._create_prompt(bucket.prefix_tokens, faker) + for _ in range(bucket.prefix_count) + ] + sample_count = percent // common_divisor + prefixes.extend([bucket_prefixes] * sample_count) + + while True: + yield rand.choice(prefixes) + @DatasetDeserializerFactory.register("synthetic_text") class SyntheticTextDatasetDeserializer(DatasetDeserializer): From 07da84fd6e54bb5d6f8a41976d943a7a2bcb43c4 Mon Sep 17 00:00:00 2001 From: Samuel Monson Date: Thu, 2 Oct 2025 13:51:03 -0400 Subject: [PATCH 06/10] Smarter weighing Signed-off-by: Samuel Monson --- src/guidellm/data/deserializers/synthetic.py | 34 +++++++------------- 1 file changed, 12 insertions(+), 22 deletions(-) diff --git a/src/guidellm/data/deserializers/synthetic.py b/src/guidellm/data/deserializers/synthetic.py index bfd61e7d..b0d7a33c 100644 --- a/src/guidellm/data/deserializers/synthetic.py +++ b/src/guidellm/data/deserializers/synthetic.py @@ -1,10 +1,10 @@ from __future__ import annotations +import math from collections.abc import Iterator -from math import gcd from pathlib import Path from random import Random -from typing import Any, Callable, ClassVar +from typing import Any, Callable import yaml from datasets import Features, IterableDataset, Value @@ -95,8 +95,6 @@ class SyntheticTextDatasetConfig(StandardBaseModel): class SyntheticTextGenerator: - PREFIX_DISTRIBUTION_PRECISION: ClassVar[int] = 1000 - def __init__( self, config: SyntheticTextDatasetConfig, @@ -174,34 +172,26 @@ def _create_prefix_iter(self, faker: Faker, rand: Random) -> Iterator[str]: while True: yield "" - total_weight = sum( - bucket.bucket_weight for bucket in self.config.prefix_buckets + # Increase weights to ensure an integer number of samples per per-prefix + least_common_prefix_count = math.lcm( + *(bucket.prefix_count for bucket in self.config.prefix_buckets) ) - if total_weight <= 0: - raise ValueError("Total weight of prefix buckets must be greater than 0.") - - # Calculate the divisor needed to achieve the minimum - # number of prompts given the weight ratios - percents = [ - int( - self.PREFIX_DISTRIBUTION_PRECISION - * bucket.bucket_weight - / bucket.prefix_count - / total_weight - ) + unnorm_weights = [ + least_common_prefix_count * bucket.bucket_weight // bucket.prefix_count for bucket in self.config.prefix_buckets ] - common_divisor = gcd(*percents) + # Use GCD to reduce the weights to smallest integer ratio + common_divisor = math.gcd(*unnorm_weights) # Create prefix list maintaining the correct distribution prefixes = [] - for bucket, percent in zip(self.config.prefix_buckets, percents): + for bucket, weight in zip(self.config.prefix_buckets, unnorm_weights): bucket_prefixes = [ self._create_prompt(bucket.prefix_tokens, faker) for _ in range(bucket.prefix_count) ] - sample_count = percent // common_divisor - prefixes.extend([bucket_prefixes] * sample_count) + sample_count = weight // common_divisor + prefixes.extend(bucket_prefixes * sample_count) while True: yield rand.choice(prefixes) From 2588cdaa0260a395f10e5360dbadc22a8a0aac42 Mon Sep 17 00:00:00 2001 From: Samuel Monson Date: Thu, 2 Oct 2025 16:31:17 -0400 Subject: [PATCH 07/10] Support setting initial prefix_bucket from top level config Signed-off-by: Samuel Monson --- src/guidellm/data/deserializers/synthetic.py | 30 ++++++++++++++++++-- 1 file changed, 27 insertions(+), 3 deletions(-) diff --git a/src/guidellm/data/deserializers/synthetic.py b/src/guidellm/data/deserializers/synthetic.py index b0d7a33c..a071eeea 100644 --- a/src/guidellm/data/deserializers/synthetic.py +++ b/src/guidellm/data/deserializers/synthetic.py @@ -4,12 +4,12 @@ from collections.abc import Iterator from pathlib import Path from random import Random -from typing import Any, Callable +from typing import Any, Callable, Self import yaml from datasets import Features, IterableDataset, Value from faker import Faker -from pydantic import Field +from pydantic import ConfigDict, Field, model_validator from transformers import PreTrainedTokenizerBase from guidellm.data.deserializers.deserializer import ( @@ -34,7 +34,7 @@ class SyntheticTextPrefixBucketConfig(StandardBaseModel): default=100, ) prefix_count: int = Field( - description="The number of unique prefixs to generate for this bucket.", + description="The number of unique prefixes to generate for this bucket.", ge=1, default=1, ) @@ -46,6 +46,10 @@ class SyntheticTextPrefixBucketConfig(StandardBaseModel): class SyntheticTextDatasetConfig(StandardBaseModel): + model_config = ConfigDict( + extra="allow", + ) + prefix_buckets: list[SyntheticTextPrefixBucketConfig] | None = Field( description="Buckets for the prefix tokens distribution.", default=None, @@ -93,6 +97,26 @@ class SyntheticTextDatasetConfig(StandardBaseModel): default="data:prideandprejudice.txt.gz", ) + @model_validator(mode="after") + def check_prefix_options(self) -> Self: + prefix_count = self.__pydantic_extra__.get("prefix_count", None) # type: ignore[attr-defined] + prefix_tokens = self.__pydantic_extra__.get("prefix_count", None) # type: ignore[attr-defined] + if prefix_count is not None or prefix_tokens is not None: + if self.prefix_buckets: + raise ValueError( + "prefix_buckets is mutually exclusive" + " with prefix_count and prefix_tokens" + ) + + self.prefix_buckets = [ + SyntheticTextPrefixBucketConfig( + prefix_count=prefix_count or 1, + prefix_tokens=prefix_tokens or 0, + ) + ] + + return self + class SyntheticTextGenerator: def __init__( From b9fec8030c21951d20c96bcd580aa3c948da4fc5 Mon Sep 17 00:00:00 2001 From: Samuel Monson Date: Tue, 19 Aug 2025 15:48:19 -0400 Subject: [PATCH 08/10] Port tests from old adv_prefix branch Signed-off-by: Samuel Monson --- tests/unit/dataset/test_synthetic.py | 416 ++++++++++++++++++--------- 1 file changed, 282 insertions(+), 134 deletions(-) diff --git a/tests/unit/dataset/test_synthetic.py b/tests/unit/dataset/test_synthetic.py index e3110fa3..080fcbfb 100644 --- a/tests/unit/dataset/test_synthetic.py +++ b/tests/unit/dataset/test_synthetic.py @@ -11,12 +11,83 @@ import yaml from guidellm.dataset.synthetic import ( + PrefixBucketConfig, SyntheticDatasetConfig, SyntheticDatasetCreator, SyntheticTextItemsGenerator, ) +class TestPrefixBucketConfig: + """Test cases for PrefixBucketConfig class. + + ### WRITTEN BY AI ### + """ + + @pytest.mark.smoke + def test_creation_with_valid_params(self): + """Test creating PrefixBucketConfig with valid parameters. + + ### WRITTEN BY AI ### + """ + config = PrefixBucketConfig(bucket_weight=100, prefix_count=1, prefix_tokens=5) + + assert config.bucket_weight == 100 + assert config.prefix_count == 1 + assert config.prefix_tokens == 5 + + @pytest.mark.sanity + def test_creation_with_negative_values(self): + """Test creating PrefixBucketConfig with negative values raises ValueError. + + ### WRITTEN BY AI ### + """ + with pytest.raises(ValueError): + PrefixBucketConfig(bucket_weight=-10, prefix_count=1, prefix_tokens=5) + + with pytest.raises(ValueError): + PrefixBucketConfig(bucket_weight=100, prefix_count=-1, prefix_tokens=5) + + with pytest.raises(ValueError): + PrefixBucketConfig(bucket_weight=100, prefix_count=1, prefix_tokens=-5) + + @pytest.mark.regression + def test_prefix_bucket_zero_weight_error(self): + """Test that zero total weight raises an error. + + ### WRITTEN BY AI ### + """ + # Test validation error for creating PrefixBucketConfig with weight=0 + with pytest.raises(ValueError): + PrefixBucketConfig(bucket_weight=0, prefix_count=1, prefix_tokens=2) + + @pytest.mark.sanity + def test_prefix_bucket_config_validation(self): + """Test PrefixBucketConfig validation. + + ### WRITTEN BY AI ### + """ + # Test valid config + valid_config = PrefixBucketConfig( + bucket_weight=50, prefix_count=2, prefix_tokens=3 + ) + assert valid_config.bucket_weight == 50 + assert valid_config.prefix_count == 2 + assert valid_config.prefix_tokens == 3 + + # Test invalid bucket_weight + with pytest.raises(ValueError): + PrefixBucketConfig(bucket_weight=0, prefix_count=1, prefix_tokens=2) + + # Test invalid prefix_count + with pytest.raises(ValueError): + PrefixBucketConfig(bucket_weight=100, prefix_count=0, prefix_tokens=2) + + # Test invalid prefix_tokens + with pytest.raises(ValueError): + PrefixBucketConfig(bucket_weight=100, prefix_count=1, prefix_tokens=-1) + + class TestSyntheticDatasetConfig: """Test cases for SyntheticDatasetConfig class. @@ -29,8 +100,12 @@ def test_config_creation_with_all_params(self): ### WRITTEN BY AI ### """ + prefix_bucket = PrefixBucketConfig( + bucket_weight=100, prefix_count=1, prefix_tokens=5 + ) + config = SyntheticDatasetConfig( - prefix_tokens=5, + prefix_buckets=[prefix_bucket], prompt_tokens=100, prompt_tokens_stdev=10, prompt_tokens_min=50, @@ -43,7 +118,7 @@ def test_config_creation_with_all_params(self): source="custom_text.txt", ) - assert config.prefix_tokens == 5 + assert config.prefix_buckets[0].prefix_tokens == 5 # type: ignore [index] assert config.prompt_tokens == 100 assert config.prompt_tokens_stdev == 10 assert config.prompt_tokens_min == 50 @@ -67,7 +142,9 @@ def test_parse_json_string(self): "output_tokens": 25, "samples": 200, "source": "test.txt", - "prefix_tokens": 10, + "prefix_buckets": [ + {"bucket_weight": 100, "prefix_count": 1, "prefix_tokens": 10} + ], } ) @@ -77,7 +154,7 @@ def test_parse_json_string(self): assert config.output_tokens == 25 assert config.samples == 200 assert config.source == "test.txt" - assert config.prefix_tokens == 10 + assert config.prefix_buckets[0].prefix_tokens == 10 # type: ignore [index] @pytest.mark.regression def test_parse_key_value_pairs(self): @@ -85,7 +162,7 @@ def test_parse_key_value_pairs(self): ### WRITTEN BY AI ### """ - kv_str = "prompt_tokens=80,output_tokens=30,samples=300,source=data.txt,prefix_tokens=5" # noqa: E501 + kv_str = "prompt_tokens=80,output_tokens=30,samples=300,source=data.txt" config = SyntheticDatasetConfig.parse_str(kv_str) @@ -93,7 +170,7 @@ def test_parse_key_value_pairs(self): assert config.output_tokens == 30 assert config.samples == 300 assert config.source == "data.txt" - assert config.prefix_tokens == 5 + assert config.prefix_buckets is None @pytest.mark.sanity def test_parse_yaml_file(self): @@ -106,7 +183,9 @@ def test_parse_yaml_file(self): "output_tokens": 15, "samples": 100, "source": "yaml_test.txt", - "prefix_tokens": 3, + "prefix_buckets": [ + {"bucket_weight": 100, "prefix_count": 1, "prefix_tokens": 3} + ], } with tempfile.NamedTemporaryFile(mode="w", suffix=".yaml", delete=False) as f: @@ -120,7 +199,7 @@ def test_parse_yaml_file(self): assert config.output_tokens == 15 assert config.samples == 100 assert config.source == "yaml_test.txt" - assert config.prefix_tokens == 3 + assert config.prefix_buckets[0].prefix_tokens == 3 # type: ignore [index] finally: Path(yaml_path).unlink() @@ -134,7 +213,9 @@ def test_parse_config_file(self): "prompt_tokens": 90, "output_tokens": 35, "samples": 150, - "prefix_tokens": 2, + "prefix_buckets": [ + {"bucket_weight": 100, "prefix_count": 1, "prefix_tokens": 2} + ], } with tempfile.NamedTemporaryFile(mode="w", suffix=".config", delete=False) as f: @@ -147,7 +228,7 @@ def test_parse_config_file(self): assert config.prompt_tokens == 90 assert config.output_tokens == 35 assert config.samples == 150 - assert config.prefix_tokens == 2 + assert config.prefix_buckets[0].prefix_tokens == 2 # type: ignore [index] finally: Path(config_path).unlink() @@ -194,8 +275,9 @@ def test_validation_positive_values(self): with pytest.raises(ValueError): SyntheticDatasetConfig(prompt_tokens=20, output_tokens=10, samples=0) + # Test negative prefix tokens via PrefixBucketConfig validation with pytest.raises(ValueError): - SyntheticDatasetConfig(prompt_tokens=20, output_tokens=10, prefix_tokens=-1) + PrefixBucketConfig(prefix_tokens=-1) @pytest.mark.regression def test_validation_optional_positive_values(self): @@ -279,7 +361,7 @@ def mock_tokenizer(self): """ tokenizer = Mock() tokenizer.get_vocab.return_value = {f"token_{i}": i for i in range(1000)} - tokenizer.encode.side_effect = lambda text: [1, 2, 3] * (len(text) // 10 + 1) + tokenizer.encode.side_effect = lambda text: list(range(len(text.split()))) tokenizer.decode.side_effect = ( lambda tokens, skip_special_tokens=False: " ".join( f"token_{t}" for t in tokens[:5] @@ -287,6 +369,23 @@ def mock_tokenizer(self): ) return tokenizer + @pytest.fixture + def mock_integer_range_sampler(self): + """Fixture to provide a mocked IntegerRangeSampler. + + ### WRITTEN BY AI ### + """ + with patch("guidellm.dataset.synthetic.IntegerRangeSampler") as mock_sampler: + # Side effect for basic iteration with enough values for larger tests + def mock_sampler_side_effect(*args, **kwargs): + mock_instance = Mock() + # Provide enough values for tests (up to 20 items) + mock_instance.__iter__ = Mock(return_value=iter([15] * 20)) + return mock_instance + + mock_sampler.side_effect = mock_sampler_side_effect + yield mock_sampler + @pytest.fixture def simple_config(self): """Fixture for simple configuration. @@ -306,14 +405,57 @@ def config_with_prefix(self): ### WRITTEN BY AI ### """ + prefix_bucket = PrefixBucketConfig( + bucket_weight=100, prefix_count=1, prefix_tokens=3 + ) + return SyntheticDatasetConfig( - prefix_tokens=3, + prefix_buckets=[prefix_bucket], prompt_tokens=15, output_tokens=10, samples=5, source="The quick brown fox jumps over the lazy dog.", ) + @pytest.fixture + def config_with_multiple_prefix_buckets(self): + """Fixture for configuration with multiple prefix buckets. + + ### WRITTEN BY AI ### + """ + prefix_bucket1 = PrefixBucketConfig( + bucket_weight=60, prefix_count=1, prefix_tokens=2 + ) + prefix_bucket2 = PrefixBucketConfig( + bucket_weight=40, prefix_count=1, prefix_tokens=4 + ) + + return SyntheticDatasetConfig( + prefix_buckets=[prefix_bucket1, prefix_bucket2], + prompt_tokens=10, + output_tokens=5, + samples=10, + source="The quick brown fox jumps over the lazy dog.", + ) + + @pytest.fixture + def config_with_multiple_prefix_counts(self): + """Fixture for configuration with prefix_count > 1. + + ### WRITTEN BY AI ### + """ + prefix_bucket = PrefixBucketConfig( + bucket_weight=100, prefix_count=3, prefix_tokens=2 + ) + + return SyntheticDatasetConfig( + prefix_buckets=[prefix_bucket], + prompt_tokens=8, + output_tokens=4, + samples=6, + source="The quick brown fox jumps over the lazy dog.", + ) + @pytest.fixture def complex_config(self): """Fixture for complex configuration with variance. @@ -352,29 +494,16 @@ def test_generator_initialization( mock_text_creator.assert_called_once_with(data=simple_config.source) @pytest.mark.smoke - @patch("guidellm.dataset.synthetic.EndlessTextCreator") - @patch("guidellm.dataset.synthetic.IntegerRangeSampler") def test_basic_iteration( - self, mock_sampler, mock_text_creator, simple_config, mock_tokenizer + self, + mock_integer_range_sampler, + simple_config, + mock_tokenizer, ): """Test basic iteration functionality. ### WRITTEN BY AI ### """ - # Setup mocks - mock_text_creator_instance = Mock() - mock_text_creator_instance.words = ["word1", "word2", "word3"] * 100 - mock_text_creator_instance.create_text.return_value = "sample text" - mock_text_creator.return_value = mock_text_creator_instance - - # Mock IntegerRangeSampler to return iterators - def mock_sampler_side_effect(*args, **kwargs): - mock_instance = Mock() - mock_instance.__iter__ = Mock(return_value=iter([15, 15, 15, 15, 15])) - return mock_instance - - mock_sampler.side_effect = mock_sampler_side_effect - generator = SyntheticTextItemsGenerator( simple_config, mock_tokenizer, random_seed=42 ) @@ -394,28 +523,19 @@ def mock_sampler_side_effect(*args, **kwargs): assert isinstance(item["output_tokens_count"], int) @pytest.mark.sanity - @patch("guidellm.dataset.synthetic.EndlessTextCreator") - def test_create_prompt_method( - self, mock_text_creator, simple_config, mock_tokenizer - ): + def test_create_prompt_method(self, simple_config, mock_tokenizer): """Test _create_prompt method. ### WRITTEN BY AI ### """ - mock_text_creator_instance = Mock() - mock_text_creator_instance.words = ["word"] * 100 - mock_text_creator_instance.create_text.return_value = "test text" - mock_text_creator.return_value = mock_text_creator_instance - - mock_tokenizer.encode.return_value = [1, 2, 3] - generator = SyntheticTextItemsGenerator( simple_config, mock_tokenizer, random_seed=42 ) # Test normal case result = generator._create_prompt(5, 0, 42) - assert result == [42, 1, 2, 3] + assert result[0] == 42 # Unique prefix token + assert len(result) == 5 # Test zero tokens result = generator._create_prompt(0, 0, 42) @@ -423,30 +543,14 @@ def test_create_prompt_method( # Test without unique prefix result = generator._create_prompt(3, 0) - assert result == [1, 2, 3] + assert len(result) == 3 @pytest.mark.regression - @patch("guidellm.dataset.synthetic.EndlessTextCreator") - def test_create_prompt_binary_search( - self, mock_text_creator, simple_config, mock_tokenizer - ): + def test_create_prompt_binary_search(self, simple_config, mock_tokenizer): """Test binary search logic in _create_prompt. ### WRITTEN BY AI ### """ - mock_text_creator_instance = Mock() - mock_text_creator_instance.words = ["word"] * 1000 - mock_text_creator_instance.create_text.side_effect = lambda start, length: ( - "text " * max(1, length // 4) - ).strip() - mock_text_creator.return_value = mock_text_creator_instance - - # Mock tokenizer to return different lengths based on input - def mock_encode(text): - return [1] * len(text.split()) - - mock_tokenizer.encode.side_effect = mock_encode - generator = SyntheticTextItemsGenerator( simple_config, mock_tokenizer, random_seed=42 ) @@ -456,25 +560,13 @@ def mock_encode(text): assert len(result) >= 4 # Should include prefix + some tokens @pytest.mark.sanity - @patch("guidellm.dataset.synthetic.EndlessTextCreator") - @patch("guidellm.dataset.synthetic.IntegerRangeSampler") def test_prefix_tokens_integration( - self, mock_sampler, mock_text_creator, config_with_prefix, mock_tokenizer + self, mock_integer_range_sampler, config_with_prefix, mock_tokenizer ): """Test integration with prefix tokens. ### WRITTEN BY AI ### """ - # Setup mocks - mock_text_creator_instance = Mock() - mock_text_creator_instance.words = ["word"] * 100 - mock_text_creator_instance.create_text.return_value = "sample text" - mock_text_creator.return_value = mock_text_creator_instance - - mock_sampler_instance = Mock() - mock_sampler_instance.__iter__ = Mock(return_value=iter([15, 15, 15, 15, 15])) - mock_sampler.return_value = mock_sampler_instance - generator = SyntheticTextItemsGenerator( config_with_prefix, mock_tokenizer, random_seed=42 ) @@ -483,40 +575,19 @@ def test_prefix_tokens_integration( # Verify prompt_tokens_count includes prefix for item in items: - assert item["prompt_tokens_count"] == config_with_prefix.prefix_tokens + 15 + assert ( + item["prompt_tokens_count"] + == config_with_prefix.prefix_buckets[0].prefix_tokens + 15 + ) @pytest.mark.regression - @patch("guidellm.dataset.synthetic.EndlessTextCreator") - @patch("guidellm.dataset.synthetic.IntegerRangeSampler") def test_random_seeding_consistency( - self, mock_sampler, mock_text_creator, simple_config, mock_tokenizer + self, mock_integer_range_sampler, simple_config, mock_tokenizer ): """Test that same seed produces consistent results. ### WRITTEN BY AI ### """ - # Setup mocks - mock_text_creator_instance = Mock() - mock_text_creator_instance.words = ["word"] * 100 - mock_text_creator_instance.create_text.return_value = "sample text" - mock_text_creator.return_value = mock_text_creator_instance - - # Create consistent mock sampler behavior - call_count = 0 - - def mock_sampler_side_effect(*args, **kwargs): - nonlocal call_count - mock_instance = Mock() - # Return same sequence for both prompt and output tokens - if call_count % 2 == 0: # prompt tokens - mock_instance.__iter__ = Mock(return_value=iter([15, 16, 17, 18, 19])) - else: # output tokens - mock_instance.__iter__ = Mock(return_value=iter([10, 11, 12, 13, 14])) - call_count += 1 - return mock_instance - - mock_sampler.side_effect = mock_sampler_side_effect - # Create two generators with same seed generator1 = SyntheticTextItemsGenerator( simple_config, mock_tokenizer, random_seed=42 @@ -528,7 +599,7 @@ def mock_sampler_side_effect(*args, **kwargs): items1 = list(generator1) items2 = list(generator2) - # Results should be identical with same seed + # With same seed and deterministic mocks, results should be identical assert len(items1) == len(items2) for item1, item2 in zip(items1, items2): assert item1["prompt"] == item2["prompt"] @@ -536,34 +607,13 @@ def mock_sampler_side_effect(*args, **kwargs): assert item1["output_tokens_count"] == item2["output_tokens_count"] @pytest.mark.regression - @patch("guidellm.dataset.synthetic.EndlessTextCreator") - @patch("guidellm.dataset.synthetic.IntegerRangeSampler") def test_variance_configuration( - self, mock_sampler, mock_text_creator, complex_config, mock_tokenizer + self, mock_integer_range_sampler, complex_config, mock_tokenizer ): """Test that variance configuration is properly used. ### WRITTEN BY AI ### """ - # Setup mocks - mock_text_creator_instance = Mock() - mock_text_creator_instance.words = ["word"] * 100 - mock_text_creator_instance.create_text.return_value = "sample text" - mock_text_creator.return_value = mock_text_creator_instance - - # Fix tokenizer mock to handle the create_text return properly - mock_tokenizer.encode.side_effect = ( - lambda text: [1, 2, 3] if isinstance(text, str) else [1, 2, 3] - ) - - # Setup mock sampler to track calls - def mock_sampler_side_effect(*args, **kwargs): - mock_instance = Mock() - mock_instance.__iter__ = Mock(return_value=iter([20, 18, 22, 19, 21] * 2)) - return mock_instance - - mock_sampler.side_effect = mock_sampler_side_effect - generator = SyntheticTextItemsGenerator( complex_config, mock_tokenizer, random_seed=42 ) @@ -573,10 +623,10 @@ def mock_sampler_side_effect(*args, **kwargs): next(generator_iter) # Verify that IntegerRangeSampler is called with correct parameters - assert mock_sampler.call_count == 2 + assert mock_integer_range_sampler.call_count == 2 # Check prompt tokens sampler call - prompt_call = mock_sampler.call_args_list[0] + prompt_call = mock_integer_range_sampler.call_args_list[0] assert prompt_call[1]["average"] == complex_config.prompt_tokens assert prompt_call[1]["variance"] == complex_config.prompt_tokens_stdev assert prompt_call[1]["min_value"] == complex_config.prompt_tokens_min @@ -584,7 +634,7 @@ def mock_sampler_side_effect(*args, **kwargs): assert prompt_call[1]["random_seed"] == 42 # Check output tokens sampler call - output_call = mock_sampler.call_args_list[1] + output_call = mock_integer_range_sampler.call_args_list[1] assert output_call[1]["average"] == complex_config.output_tokens assert output_call[1]["variance"] == complex_config.output_tokens_stdev assert output_call[1]["min_value"] == complex_config.output_tokens_min @@ -592,19 +642,11 @@ def mock_sampler_side_effect(*args, **kwargs): assert output_call[1]["random_seed"] == 43 # 42 + 1 @pytest.mark.regression - @patch("guidellm.dataset.synthetic.EndlessTextCreator") - def test_unique_prefix_generation( - self, mock_text_creator, simple_config, mock_tokenizer - ): + def test_unique_prefix_generation(self, simple_config, mock_tokenizer): """Test that unique prefixes are generated for each request. ### WRITTEN BY AI ### """ - mock_text_creator_instance = Mock() - mock_text_creator_instance.words = ["word"] * 100 - mock_text_creator_instance.create_text.return_value = "sample text" - mock_text_creator.return_value = mock_text_creator_instance - # Mock the cycle to return predictable values with patch("guidellm.dataset.synthetic.cycle") as mock_cycle: mock_cycle.return_value = iter([100, 101, 102, 103, 104]) @@ -620,6 +662,112 @@ def test_unique_prefix_generation( # Verify cycle was called with vocab values mock_cycle.assert_called_once() + @pytest.mark.regression + def test_multiple_prefix_buckets_distribution( + self, + mock_integer_range_sampler, + config_with_multiple_prefix_buckets, + mock_tokenizer, + ): + """Test distribution across multiple prefix buckets with different weights. + + ### WRITTEN BY AI ### + """ + generator = SyntheticTextItemsGenerator( + config_with_multiple_prefix_buckets, mock_tokenizer, random_seed=42 + ) + + items = list(generator) + + # Verify we get the expected number of items + assert len(items) == config_with_multiple_prefix_buckets.samples + + # Verify that prefix tokens are added to prompt_tokens_count + # Since we have buckets with 2 and 4 prefix tokens, and the mock returns 15 + # prompt tokens, we should see prompt_tokens_count of either 17 or 19 + prefix_counts = [item["prompt_tokens_count"] for item in items] + assert all(count in [17, 19] for count in prefix_counts) + + # Calculate expected distribution based on weights + # Bucket 1: weight=60, prefix_count=1, prefix_tokens=2 + # Bucket 2: weight=40, prefix_count=1, prefix_tokens=4 + # Total weight = 100, samples = 10 + # Bucket 1: (60/1/100) * 10 = 6 samples with 17 tokens (2 prefix + 15 prompt) + # Bucket 2: (40/1/100) * 10 = 4 samples with 19 tokens (4 prefix + 15 prompt) + count_17 = prefix_counts.count(17) # 2 prefix tokens + count_19 = prefix_counts.count(19) # 4 prefix tokens + assert count_17 == 6 + assert count_19 == 4 + + @pytest.mark.regression + def test_multiple_prefix_counts( + self, + mock_integer_range_sampler, + config_with_multiple_prefix_counts, + mock_tokenizer, + ): + """Test prefix buckets with prefix_count > 1. + + ### WRITTEN BY AI ### + """ + generator = SyntheticTextItemsGenerator( + config_with_multiple_prefix_counts, mock_tokenizer, random_seed=42 + ) + + items = list(generator) + + # Verify we get the expected number of items + assert len(items) == config_with_multiple_prefix_counts.samples + + # All items should have 2 prefix tokens + 15 prompt tokens = 17 total + for item in items: + assert item["prompt_tokens_count"] == 17 + + @pytest.mark.sanity + def test_prefix_buckets_create_prefixes_method( + self, config_with_multiple_prefix_buckets, mock_tokenizer + ): + """Test the _create_prefixes method directly. + + ### WRITTEN BY AI ### + """ + generator = SyntheticTextItemsGenerator( + config_with_multiple_prefix_buckets, mock_tokenizer, random_seed=42 + ) + + # Test _create_prefixes method + rand = Mock() + rand.randint = Mock(return_value=0) + prefixes = generator._create_prefixes(rand) + + # Should return a sequence of prefix token lists + assert isinstance(prefixes, list) + assert len(prefixes) == 10 + + # Each prefix should be a list of integers + for prefix in prefixes: + assert isinstance(prefix, list) + assert all(isinstance(token, int) for token in prefix) + + @pytest.mark.regression + def test_empty_prefix_buckets( + self, mock_integer_range_sampler, simple_config, mock_tokenizer + ): + """Test behavior when prefix_buckets is None or empty. + + ### WRITTEN BY AI ### + """ + # Test with None prefix_buckets (simple_config has None) + generator = SyntheticTextItemsGenerator( + simple_config, mock_tokenizer, random_seed=42 + ) + + items = list(generator) + + # All items should have exactly the prompt tokens (no prefix) + for item in items: + assert item["prompt_tokens_count"] == 15 # Mock returns 15 + class TestSyntheticDatasetCreator: """Test cases for SyntheticDatasetCreator class. From 59d0dad5b39c0610f279ebfbc0480bd03cbe4f74 Mon Sep 17 00:00:00 2001 From: Samuel Monson Date: Thu, 2 Oct 2025 17:07:12 -0400 Subject: [PATCH 09/10] Move tests/unit/dataset -> tests/unit/data --- tests/unit/{dataset => data}/__init__.py | 0 tests/unit/data/deserializers/__init__.py | 0 .../deserializers}/test_synthetic.py | 148 +++++++++--------- 3 files changed, 74 insertions(+), 74 deletions(-) rename tests/unit/{dataset => data}/__init__.py (100%) create mode 100644 tests/unit/data/deserializers/__init__.py rename tests/unit/{dataset => data/deserializers}/test_synthetic.py (86%) diff --git a/tests/unit/dataset/__init__.py b/tests/unit/data/__init__.py similarity index 100% rename from tests/unit/dataset/__init__.py rename to tests/unit/data/__init__.py diff --git a/tests/unit/data/deserializers/__init__.py b/tests/unit/data/deserializers/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/tests/unit/dataset/test_synthetic.py b/tests/unit/data/deserializers/test_synthetic.py similarity index 86% rename from tests/unit/dataset/test_synthetic.py rename to tests/unit/data/deserializers/test_synthetic.py index 080fcbfb..af3ac825 100644 --- a/tests/unit/dataset/test_synthetic.py +++ b/tests/unit/data/deserializers/test_synthetic.py @@ -10,11 +10,11 @@ import pytest import yaml -from guidellm.dataset.synthetic import ( - PrefixBucketConfig, - SyntheticDatasetConfig, - SyntheticDatasetCreator, - SyntheticTextItemsGenerator, +from guidellm.data.deserializers.synthetic import ( + SyntheticTextPrefixBucketConfig, + SyntheticTextDatasetConfig, + SyntheticTextDatasetDeserializer, + SyntheticTextGenerator, ) @@ -30,7 +30,7 @@ def test_creation_with_valid_params(self): ### WRITTEN BY AI ### """ - config = PrefixBucketConfig(bucket_weight=100, prefix_count=1, prefix_tokens=5) + config = SyntheticTextPrefixBucketConfig(bucket_weight=100, prefix_count=1, prefix_tokens=5) assert config.bucket_weight == 100 assert config.prefix_count == 1 @@ -43,13 +43,13 @@ def test_creation_with_negative_values(self): ### WRITTEN BY AI ### """ with pytest.raises(ValueError): - PrefixBucketConfig(bucket_weight=-10, prefix_count=1, prefix_tokens=5) + SyntheticTextPrefixBucketConfig(bucket_weight=-10, prefix_count=1, prefix_tokens=5) with pytest.raises(ValueError): - PrefixBucketConfig(bucket_weight=100, prefix_count=-1, prefix_tokens=5) + SyntheticTextPrefixBucketConfig(bucket_weight=100, prefix_count=-1, prefix_tokens=5) with pytest.raises(ValueError): - PrefixBucketConfig(bucket_weight=100, prefix_count=1, prefix_tokens=-5) + SyntheticTextPrefixBucketConfig(bucket_weight=100, prefix_count=1, prefix_tokens=-5) @pytest.mark.regression def test_prefix_bucket_zero_weight_error(self): @@ -59,7 +59,7 @@ def test_prefix_bucket_zero_weight_error(self): """ # Test validation error for creating PrefixBucketConfig with weight=0 with pytest.raises(ValueError): - PrefixBucketConfig(bucket_weight=0, prefix_count=1, prefix_tokens=2) + SyntheticTextPrefixBucketConfig(bucket_weight=0, prefix_count=1, prefix_tokens=2) @pytest.mark.sanity def test_prefix_bucket_config_validation(self): @@ -68,7 +68,7 @@ def test_prefix_bucket_config_validation(self): ### WRITTEN BY AI ### """ # Test valid config - valid_config = PrefixBucketConfig( + valid_config = SyntheticTextPrefixBucketConfig( bucket_weight=50, prefix_count=2, prefix_tokens=3 ) assert valid_config.bucket_weight == 50 @@ -77,15 +77,15 @@ def test_prefix_bucket_config_validation(self): # Test invalid bucket_weight with pytest.raises(ValueError): - PrefixBucketConfig(bucket_weight=0, prefix_count=1, prefix_tokens=2) + SyntheticTextPrefixBucketConfig(bucket_weight=0, prefix_count=1, prefix_tokens=2) # Test invalid prefix_count with pytest.raises(ValueError): - PrefixBucketConfig(bucket_weight=100, prefix_count=0, prefix_tokens=2) + SyntheticTextPrefixBucketConfig(bucket_weight=100, prefix_count=0, prefix_tokens=2) # Test invalid prefix_tokens with pytest.raises(ValueError): - PrefixBucketConfig(bucket_weight=100, prefix_count=1, prefix_tokens=-1) + SyntheticTextPrefixBucketConfig(bucket_weight=100, prefix_count=1, prefix_tokens=-1) class TestSyntheticDatasetConfig: @@ -100,11 +100,11 @@ def test_config_creation_with_all_params(self): ### WRITTEN BY AI ### """ - prefix_bucket = PrefixBucketConfig( + prefix_bucket = SyntheticTextPrefixBucketConfig( bucket_weight=100, prefix_count=1, prefix_tokens=5 ) - config = SyntheticDatasetConfig( + config = SyntheticTextDatasetConfig( prefix_buckets=[prefix_bucket], prompt_tokens=100, prompt_tokens_stdev=10, @@ -148,7 +148,7 @@ def test_parse_json_string(self): } ) - config = SyntheticDatasetConfig.parse_str(json_str) + config = SyntheticTextDatasetConfig.parse_str(json_str) assert config.prompt_tokens == 75 assert config.output_tokens == 25 @@ -164,7 +164,7 @@ def test_parse_key_value_pairs(self): """ kv_str = "prompt_tokens=80,output_tokens=30,samples=300,source=data.txt" - config = SyntheticDatasetConfig.parse_str(kv_str) + config = SyntheticTextDatasetConfig.parse_str(kv_str) assert config.prompt_tokens == 80 assert config.output_tokens == 30 @@ -193,7 +193,7 @@ def test_parse_yaml_file(self): yaml_path = f.name try: - config = SyntheticDatasetConfig.parse_str(yaml_path) + config = SyntheticTextDatasetConfig.parse_str(yaml_path) assert config.prompt_tokens == 60 assert config.output_tokens == 15 @@ -223,7 +223,7 @@ def test_parse_config_file(self): config_path = f.name try: - config = SyntheticDatasetConfig.parse_str(config_path) + config = SyntheticTextDatasetConfig.parse_str(config_path) assert config.prompt_tokens == 90 assert config.output_tokens == 35 @@ -245,7 +245,7 @@ def test_parse_path_object(self): yaml_path = Path(f.name) try: - config = SyntheticDatasetConfig.parse_str(yaml_path) + config = SyntheticTextDatasetConfig.parse_str(yaml_path) assert config.prompt_tokens == 45 assert config.output_tokens == 25 finally: @@ -258,7 +258,7 @@ def test_parse_invalid_format(self): ### WRITTEN BY AI ### """ with pytest.raises(ValueError, match="Unsupported data format"): - SyntheticDatasetConfig.parse_str("invalid_format_string") + SyntheticTextDatasetConfig.parse_str("invalid_format_string") @pytest.mark.sanity def test_validation_positive_values(self): @@ -267,17 +267,17 @@ def test_validation_positive_values(self): ### WRITTEN BY AI ### """ with pytest.raises(ValueError): - SyntheticDatasetConfig(prompt_tokens=0, output_tokens=20) + SyntheticTextDatasetConfig(prompt_tokens=0, output_tokens=20) with pytest.raises(ValueError): - SyntheticDatasetConfig(prompt_tokens=20, output_tokens=0) + SyntheticTextDatasetConfig(prompt_tokens=20, output_tokens=0) with pytest.raises(ValueError): - SyntheticDatasetConfig(prompt_tokens=20, output_tokens=10, samples=0) + SyntheticTextDatasetConfig(prompt_tokens=20, output_tokens=10, samples=0) # Test negative prefix tokens via PrefixBucketConfig validation with pytest.raises(ValueError): - PrefixBucketConfig(prefix_tokens=-1) + SyntheticTextPrefixBucketConfig(prefix_tokens=-1) @pytest.mark.regression def test_validation_optional_positive_values(self): @@ -286,17 +286,17 @@ def test_validation_optional_positive_values(self): ### WRITTEN BY AI ### """ with pytest.raises(ValueError): - SyntheticDatasetConfig( + SyntheticTextDatasetConfig( prompt_tokens=20, output_tokens=10, prompt_tokens_stdev=-1 ) with pytest.raises(ValueError): - SyntheticDatasetConfig( + SyntheticTextDatasetConfig( prompt_tokens=20, output_tokens=10, prompt_tokens_min=-1 ) with pytest.raises(ValueError): - SyntheticDatasetConfig( + SyntheticTextDatasetConfig( prompt_tokens=20, output_tokens=10, output_tokens_max=0 ) @@ -309,7 +309,7 @@ def test_parse_json_method_directly(self): json_data = {"prompt_tokens": 100, "output_tokens": 50} json_str = json.dumps(json_data) - config = SyntheticDatasetConfig.parse_json(json_str) + config = SyntheticTextDatasetConfig.parse_json(json_str) assert config.prompt_tokens == 100 assert config.output_tokens == 50 @@ -322,7 +322,7 @@ def test_parse_key_value_pairs_method_directly(self): """ kv_str = "prompt_tokens=75,output_tokens=35" - config = SyntheticDatasetConfig.parse_key_value_pairs(kv_str) + config = SyntheticTextDatasetConfig.parse_key_value_pairs(kv_str) assert config.prompt_tokens == 75 assert config.output_tokens == 35 @@ -340,7 +340,7 @@ def test_parse_config_file_method_directly(self): config_path = f.name try: - config = SyntheticDatasetConfig.parse_config_file(config_path) + config = SyntheticTextDatasetConfig.parse_config_file(config_path) assert config.prompt_tokens == 65 assert config.output_tokens == 45 finally: @@ -392,7 +392,7 @@ def simple_config(self): ### WRITTEN BY AI ### """ - return SyntheticDatasetConfig( + return SyntheticTextDatasetConfig( prompt_tokens=15, output_tokens=10, samples=5, @@ -405,11 +405,11 @@ def config_with_prefix(self): ### WRITTEN BY AI ### """ - prefix_bucket = PrefixBucketConfig( + prefix_bucket = SyntheticTextPrefixBucketConfig( bucket_weight=100, prefix_count=1, prefix_tokens=3 ) - return SyntheticDatasetConfig( + return SyntheticTextDatasetConfig( prefix_buckets=[prefix_bucket], prompt_tokens=15, output_tokens=10, @@ -423,14 +423,14 @@ def config_with_multiple_prefix_buckets(self): ### WRITTEN BY AI ### """ - prefix_bucket1 = PrefixBucketConfig( + prefix_bucket1 = SyntheticTextPrefixBucketConfig( bucket_weight=60, prefix_count=1, prefix_tokens=2 ) - prefix_bucket2 = PrefixBucketConfig( + prefix_bucket2 = SyntheticTextPrefixBucketConfig( bucket_weight=40, prefix_count=1, prefix_tokens=4 ) - return SyntheticDatasetConfig( + return SyntheticTextDatasetConfig( prefix_buckets=[prefix_bucket1, prefix_bucket2], prompt_tokens=10, output_tokens=5, @@ -444,11 +444,11 @@ def config_with_multiple_prefix_counts(self): ### WRITTEN BY AI ### """ - prefix_bucket = PrefixBucketConfig( + prefix_bucket = SyntheticTextPrefixBucketConfig( bucket_weight=100, prefix_count=3, prefix_tokens=2 ) - return SyntheticDatasetConfig( + return SyntheticTextDatasetConfig( prefix_buckets=[prefix_bucket], prompt_tokens=8, output_tokens=4, @@ -462,7 +462,7 @@ def complex_config(self): ### WRITTEN BY AI ### """ - return SyntheticDatasetConfig( + return SyntheticTextDatasetConfig( prompt_tokens=20, prompt_tokens_stdev=5, prompt_tokens_min=10, @@ -484,7 +484,7 @@ def test_generator_initialization( ### WRITTEN BY AI ### """ - generator = SyntheticTextItemsGenerator( + generator = SyntheticTextGenerator( simple_config, mock_tokenizer, random_seed=42 ) @@ -504,7 +504,7 @@ def test_basic_iteration( ### WRITTEN BY AI ### """ - generator = SyntheticTextItemsGenerator( + generator = SyntheticTextGenerator( simple_config, mock_tokenizer, random_seed=42 ) @@ -528,7 +528,7 @@ def test_create_prompt_method(self, simple_config, mock_tokenizer): ### WRITTEN BY AI ### """ - generator = SyntheticTextItemsGenerator( + generator = SyntheticTextGenerator( simple_config, mock_tokenizer, random_seed=42 ) @@ -551,7 +551,7 @@ def test_create_prompt_binary_search(self, simple_config, mock_tokenizer): ### WRITTEN BY AI ### """ - generator = SyntheticTextItemsGenerator( + generator = SyntheticTextGenerator( simple_config, mock_tokenizer, random_seed=42 ) @@ -567,7 +567,7 @@ def test_prefix_tokens_integration( ### WRITTEN BY AI ### """ - generator = SyntheticTextItemsGenerator( + generator = SyntheticTextGenerator( config_with_prefix, mock_tokenizer, random_seed=42 ) @@ -589,10 +589,10 @@ def test_random_seeding_consistency( ### WRITTEN BY AI ### """ # Create two generators with same seed - generator1 = SyntheticTextItemsGenerator( + generator1 = SyntheticTextGenerator( simple_config, mock_tokenizer, random_seed=42 ) - generator2 = SyntheticTextItemsGenerator( + generator2 = SyntheticTextGenerator( simple_config, mock_tokenizer, random_seed=42 ) @@ -614,7 +614,7 @@ def test_variance_configuration( ### WRITTEN BY AI ### """ - generator = SyntheticTextItemsGenerator( + generator = SyntheticTextGenerator( complex_config, mock_tokenizer, random_seed=42 ) @@ -651,7 +651,7 @@ def test_unique_prefix_generation(self, simple_config, mock_tokenizer): with patch("guidellm.dataset.synthetic.cycle") as mock_cycle: mock_cycle.return_value = iter([100, 101, 102, 103, 104]) - generator = SyntheticTextItemsGenerator( + generator = SyntheticTextGenerator( simple_config, mock_tokenizer, random_seed=42 ) @@ -673,7 +673,7 @@ def test_multiple_prefix_buckets_distribution( ### WRITTEN BY AI ### """ - generator = SyntheticTextItemsGenerator( + generator = SyntheticTextGenerator( config_with_multiple_prefix_buckets, mock_tokenizer, random_seed=42 ) @@ -710,7 +710,7 @@ def test_multiple_prefix_counts( ### WRITTEN BY AI ### """ - generator = SyntheticTextItemsGenerator( + generator = SyntheticTextGenerator( config_with_multiple_prefix_counts, mock_tokenizer, random_seed=42 ) @@ -731,7 +731,7 @@ def test_prefix_buckets_create_prefixes_method( ### WRITTEN BY AI ### """ - generator = SyntheticTextItemsGenerator( + generator = SyntheticTextGenerator( config_with_multiple_prefix_buckets, mock_tokenizer, random_seed=42 ) @@ -758,7 +758,7 @@ def test_empty_prefix_buckets( ### WRITTEN BY AI ### """ # Test with None prefix_buckets (simple_config has None) - generator = SyntheticTextItemsGenerator( + generator = SyntheticTextGenerator( simple_config, mock_tokenizer, random_seed=42 ) @@ -785,7 +785,7 @@ def test_is_supported_path_config_file(self): config_path = Path(f.name) try: - assert SyntheticDatasetCreator.is_supported(config_path, None) + assert SyntheticTextDatasetDeserializer.is_supported(config_path, None) finally: config_path.unlink() @@ -799,7 +799,7 @@ def test_is_supported_path_yaml_file(self): yaml_path = Path(f.name) try: - assert SyntheticDatasetCreator.is_supported(yaml_path, None) + assert SyntheticTextDatasetDeserializer.is_supported(yaml_path, None) finally: yaml_path.unlink() @@ -810,7 +810,7 @@ def test_is_supported_json_string(self): ### WRITTEN BY AI ### """ json_str = '{"prompt_tokens": 50, "output_tokens": 25}' - assert SyntheticDatasetCreator.is_supported(json_str, None) + assert SyntheticTextDatasetDeserializer.is_supported(json_str, None) @pytest.mark.smoke def test_is_supported_key_value_string(self): @@ -819,7 +819,7 @@ def test_is_supported_key_value_string(self): ### WRITTEN BY AI ### """ kv_str = "prompt_tokens=50,output_tokens=25" - assert SyntheticDatasetCreator.is_supported(kv_str, None) + assert SyntheticTextDatasetDeserializer.is_supported(kv_str, None) @pytest.mark.sanity def test_is_supported_config_filename_string(self): @@ -827,8 +827,8 @@ def test_is_supported_config_filename_string(self): ### WRITTEN BY AI ### """ - assert SyntheticDatasetCreator.is_supported("config.yaml", None) - assert SyntheticDatasetCreator.is_supported("settings.config", None) + assert SyntheticTextDatasetDeserializer.is_supported("config.yaml", None) + assert SyntheticTextDatasetDeserializer.is_supported("settings.config", None) @pytest.mark.sanity def test_is_not_supported_regular_string(self): @@ -836,8 +836,8 @@ def test_is_not_supported_regular_string(self): ### WRITTEN BY AI ### """ - assert not SyntheticDatasetCreator.is_supported("regular string", None) - assert not SyntheticDatasetCreator.is_supported("single=pair", None) + assert not SyntheticTextDatasetDeserializer.is_supported("regular string", None) + assert not SyntheticTextDatasetDeserializer.is_supported("single=pair", None) @pytest.mark.regression def test_is_not_supported_non_existent_path(self): @@ -846,7 +846,7 @@ def test_is_not_supported_non_existent_path(self): ### WRITTEN BY AI ### """ non_existent_path = Path("/non/existent/path.config") - assert not SyntheticDatasetCreator.is_supported(non_existent_path, None) + assert not SyntheticTextDatasetDeserializer.is_supported(non_existent_path, None) @pytest.mark.regression def test_is_not_supported_other_types(self): @@ -854,9 +854,9 @@ def test_is_not_supported_other_types(self): ### WRITTEN BY AI ### """ - assert not SyntheticDatasetCreator.is_supported(123, None) - assert not SyntheticDatasetCreator.is_supported(["list"], None) - assert not SyntheticDatasetCreator.is_supported({"dict": "value"}, None) + assert not SyntheticTextDatasetDeserializer.is_supported(123, None) + assert not SyntheticTextDatasetDeserializer.is_supported(["list"], None) + assert not SyntheticTextDatasetDeserializer.is_supported({"dict": "value"}, None) @pytest.mark.smoke @patch("guidellm.dataset.synthetic.check_load_processor") @@ -892,7 +892,7 @@ def test_handle_create_basic( # Test data = '{"prompt_tokens": 50, "output_tokens": 25}' - result = SyntheticDatasetCreator.handle_create( + result = SyntheticTextDatasetDeserializer.handle_create( data=data, data_args=None, processor="gpt2", @@ -922,7 +922,7 @@ def test_handle_create_processor_required(self, mock_check_processor): data = '{"prompt_tokens": 50, "output_tokens": 25}' with pytest.raises(ValueError, match="Processor required"): - SyntheticDatasetCreator.handle_create( + SyntheticTextDatasetDeserializer.handle_create( data=data, data_args=None, processor=None, @@ -956,7 +956,7 @@ def test_handle_create_with_data_args( data = '{"prompt_tokens": 50, "output_tokens": 25}' data_args = {"features": "custom_features"} - SyntheticDatasetCreator.handle_create( + SyntheticTextDatasetDeserializer.handle_create( data=data, data_args=data_args, processor="gpt2", @@ -973,7 +973,7 @@ def test_extract_args_column_mappings_empty(self): ### WRITTEN BY AI ### """ - result = SyntheticDatasetCreator.extract_args_column_mappings(None) + result = SyntheticTextDatasetDeserializer.extract_args_column_mappings(None) expected = { "prompt_column": "prompt", @@ -990,13 +990,13 @@ def test_extract_args_column_mappings_with_parent_mappings(self): """ with ( patch.object( - SyntheticDatasetCreator.__bases__[0], + SyntheticTextDatasetDeserializer.__bases__[0], "extract_args_column_mappings", return_value={"prompt_column": "custom_prompt"}, ), pytest.raises(ValueError, match="Column mappings are not supported"), ): - SyntheticDatasetCreator.extract_args_column_mappings({"some": "args"}) + SyntheticTextDatasetDeserializer.extract_args_column_mappings({"some": "args"}) @pytest.mark.regression def test_extract_args_column_mappings_no_parent_mappings(self): @@ -1005,11 +1005,11 @@ def test_extract_args_column_mappings_no_parent_mappings(self): ### WRITTEN BY AI ### """ with patch.object( - SyntheticDatasetCreator.__bases__[0], + SyntheticTextDatasetDeserializer.__bases__[0], "extract_args_column_mappings", return_value={}, ): - result = SyntheticDatasetCreator.extract_args_column_mappings( + result = SyntheticTextDatasetDeserializer.extract_args_column_mappings( {"some": "args"} ) From 62d6749feae3740dc66c97eb39359adbecdfbf38 Mon Sep 17 00:00:00 2001 From: Samuel Monson Date: Thu, 2 Oct 2025 17:26:30 -0400 Subject: [PATCH 10/10] Initial tests update --- .../unit/data/deserializers/test_synthetic.py | 824 +++++------------- 1 file changed, 195 insertions(+), 629 deletions(-) diff --git a/tests/unit/data/deserializers/test_synthetic.py b/tests/unit/data/deserializers/test_synthetic.py index af3ac825..58b76aee 100644 --- a/tests/unit/data/deserializers/test_synthetic.py +++ b/tests/unit/data/deserializers/test_synthetic.py @@ -1,20 +1,22 @@ """ -Unit tests for guidellm.dataset.synthetic module. +Unit tests for guidellm.data.deserializers.synthetic module. """ import json import tempfile from pathlib import Path -from unittest.mock import Mock, patch +from unittest.mock import Mock import pytest import yaml +from datasets import IterableDataset +from guidellm.data.deserializers.deserializer import DataNotSupportedError from guidellm.data.deserializers.synthetic import ( - SyntheticTextPrefixBucketConfig, SyntheticTextDatasetConfig, SyntheticTextDatasetDeserializer, SyntheticTextGenerator, + SyntheticTextPrefixBucketConfig, ) @@ -30,7 +32,9 @@ def test_creation_with_valid_params(self): ### WRITTEN BY AI ### """ - config = SyntheticTextPrefixBucketConfig(bucket_weight=100, prefix_count=1, prefix_tokens=5) + config = SyntheticTextPrefixBucketConfig( + bucket_weight=100, prefix_count=1, prefix_tokens=5 + ) assert config.bucket_weight == 100 assert config.prefix_count == 1 @@ -43,13 +47,19 @@ def test_creation_with_negative_values(self): ### WRITTEN BY AI ### """ with pytest.raises(ValueError): - SyntheticTextPrefixBucketConfig(bucket_weight=-10, prefix_count=1, prefix_tokens=5) + SyntheticTextPrefixBucketConfig( + bucket_weight=-10, prefix_count=1, prefix_tokens=5 + ) with pytest.raises(ValueError): - SyntheticTextPrefixBucketConfig(bucket_weight=100, prefix_count=-1, prefix_tokens=5) + SyntheticTextPrefixBucketConfig( + bucket_weight=100, prefix_count=-1, prefix_tokens=5 + ) with pytest.raises(ValueError): - SyntheticTextPrefixBucketConfig(bucket_weight=100, prefix_count=1, prefix_tokens=-5) + SyntheticTextPrefixBucketConfig( + bucket_weight=100, prefix_count=1, prefix_tokens=-5 + ) @pytest.mark.regression def test_prefix_bucket_zero_weight_error(self): @@ -59,7 +69,9 @@ def test_prefix_bucket_zero_weight_error(self): """ # Test validation error for creating PrefixBucketConfig with weight=0 with pytest.raises(ValueError): - SyntheticTextPrefixBucketConfig(bucket_weight=0, prefix_count=1, prefix_tokens=2) + SyntheticTextPrefixBucketConfig( + bucket_weight=0, prefix_count=1, prefix_tokens=2 + ) @pytest.mark.sanity def test_prefix_bucket_config_validation(self): @@ -77,15 +89,21 @@ def test_prefix_bucket_config_validation(self): # Test invalid bucket_weight with pytest.raises(ValueError): - SyntheticTextPrefixBucketConfig(bucket_weight=0, prefix_count=1, prefix_tokens=2) + SyntheticTextPrefixBucketConfig( + bucket_weight=0, prefix_count=1, prefix_tokens=2 + ) # Test invalid prefix_count with pytest.raises(ValueError): - SyntheticTextPrefixBucketConfig(bucket_weight=100, prefix_count=0, prefix_tokens=2) + SyntheticTextPrefixBucketConfig( + bucket_weight=100, prefix_count=0, prefix_tokens=2 + ) # Test invalid prefix_tokens with pytest.raises(ValueError): - SyntheticTextPrefixBucketConfig(bucket_weight=100, prefix_count=1, prefix_tokens=-1) + SyntheticTextPrefixBucketConfig( + bucket_weight=100, prefix_count=1, prefix_tokens=-1 + ) class TestSyntheticDatasetConfig: @@ -114,7 +132,6 @@ def test_config_creation_with_all_params(self): output_tokens_stdev=5, output_tokens_min=20, output_tokens_max=40, - samples=500, source="custom_text.txt", ) @@ -127,7 +144,6 @@ def test_config_creation_with_all_params(self): assert config.output_tokens_stdev == 5 assert config.output_tokens_min == 20 assert config.output_tokens_max == 40 - assert config.samples == 500 assert config.source == "custom_text.txt" @pytest.mark.regression @@ -140,7 +156,6 @@ def test_parse_json_string(self): { "prompt_tokens": 75, "output_tokens": 25, - "samples": 200, "source": "test.txt", "prefix_buckets": [ {"bucket_weight": 100, "prefix_count": 1, "prefix_tokens": 10} @@ -148,118 +163,13 @@ def test_parse_json_string(self): } ) - config = SyntheticTextDatasetConfig.parse_str(json_str) + config = SyntheticTextDatasetConfig.model_validate_json(json_str) assert config.prompt_tokens == 75 assert config.output_tokens == 25 - assert config.samples == 200 assert config.source == "test.txt" assert config.prefix_buckets[0].prefix_tokens == 10 # type: ignore [index] - @pytest.mark.regression - def test_parse_key_value_pairs(self): - """Test parsing key-value pairs configuration. - - ### WRITTEN BY AI ### - """ - kv_str = "prompt_tokens=80,output_tokens=30,samples=300,source=data.txt" - - config = SyntheticTextDatasetConfig.parse_str(kv_str) - - assert config.prompt_tokens == 80 - assert config.output_tokens == 30 - assert config.samples == 300 - assert config.source == "data.txt" - assert config.prefix_buckets is None - - @pytest.mark.sanity - def test_parse_yaml_file(self): - """Test parsing YAML file configuration. - - ### WRITTEN BY AI ### - """ - config_data = { - "prompt_tokens": 60, - "output_tokens": 15, - "samples": 100, - "source": "yaml_test.txt", - "prefix_buckets": [ - {"bucket_weight": 100, "prefix_count": 1, "prefix_tokens": 3} - ], - } - - with tempfile.NamedTemporaryFile(mode="w", suffix=".yaml", delete=False) as f: - yaml.dump(config_data, f) - yaml_path = f.name - - try: - config = SyntheticTextDatasetConfig.parse_str(yaml_path) - - assert config.prompt_tokens == 60 - assert config.output_tokens == 15 - assert config.samples == 100 - assert config.source == "yaml_test.txt" - assert config.prefix_buckets[0].prefix_tokens == 3 # type: ignore [index] - finally: - Path(yaml_path).unlink() - - @pytest.mark.sanity - def test_parse_config_file(self): - """Test parsing .config file. - - ### WRITTEN BY AI ### - """ - config_data = { - "prompt_tokens": 90, - "output_tokens": 35, - "samples": 150, - "prefix_buckets": [ - {"bucket_weight": 100, "prefix_count": 1, "prefix_tokens": 2} - ], - } - - with tempfile.NamedTemporaryFile(mode="w", suffix=".config", delete=False) as f: - yaml.dump(config_data, f) - config_path = f.name - - try: - config = SyntheticTextDatasetConfig.parse_str(config_path) - - assert config.prompt_tokens == 90 - assert config.output_tokens == 35 - assert config.samples == 150 - assert config.prefix_buckets[0].prefix_tokens == 2 # type: ignore [index] - finally: - Path(config_path).unlink() - - @pytest.mark.regression - def test_parse_path_object(self): - """Test parsing with Path object. - - ### WRITTEN BY AI ### - """ - config_data = {"prompt_tokens": 45, "output_tokens": 25} - - with tempfile.NamedTemporaryFile(mode="w", suffix=".yaml", delete=False) as f: - yaml.dump(config_data, f) - yaml_path = Path(f.name) - - try: - config = SyntheticTextDatasetConfig.parse_str(yaml_path) - assert config.prompt_tokens == 45 - assert config.output_tokens == 25 - finally: - yaml_path.unlink() - - @pytest.mark.sanity - def test_parse_invalid_format(self): - """Test parsing invalid format raises ValueError. - - ### WRITTEN BY AI ### - """ - with pytest.raises(ValueError, match="Unsupported data format"): - SyntheticTextDatasetConfig.parse_str("invalid_format_string") - @pytest.mark.sanity def test_validation_positive_values(self): """Test that negative or zero values are rejected. @@ -272,9 +182,6 @@ def test_validation_positive_values(self): with pytest.raises(ValueError): SyntheticTextDatasetConfig(prompt_tokens=20, output_tokens=0) - with pytest.raises(ValueError): - SyntheticTextDatasetConfig(prompt_tokens=20, output_tokens=10, samples=0) - # Test negative prefix tokens via PrefixBucketConfig validation with pytest.raises(ValueError): SyntheticTextPrefixBucketConfig(prefix_tokens=-1) @@ -300,55 +207,9 @@ def test_validation_optional_positive_values(self): prompt_tokens=20, output_tokens=10, output_tokens_max=0 ) - @pytest.mark.regression - def test_parse_json_method_directly(self): - """Test parse_json static method directly. - - ### WRITTEN BY AI ### - """ - json_data = {"prompt_tokens": 100, "output_tokens": 50} - json_str = json.dumps(json_data) - - config = SyntheticTextDatasetConfig.parse_json(json_str) - - assert config.prompt_tokens == 100 - assert config.output_tokens == 50 - - @pytest.mark.regression - def test_parse_key_value_pairs_method_directly(self): - """Test parse_key_value_pairs static method directly. - - ### WRITTEN BY AI ### - """ - kv_str = "prompt_tokens=75,output_tokens=35" - - config = SyntheticTextDatasetConfig.parse_key_value_pairs(kv_str) - assert config.prompt_tokens == 75 - assert config.output_tokens == 35 - - @pytest.mark.regression - def test_parse_config_file_method_directly(self): - """Test parse_config_file static method directly. - - ### WRITTEN BY AI ### - """ - config_data = {"prompt_tokens": 65, "output_tokens": 45} - - with tempfile.NamedTemporaryFile(mode="w", suffix=".yaml", delete=False) as f: - yaml.dump(config_data, f) - config_path = f.name - - try: - config = SyntheticTextDatasetConfig.parse_config_file(config_path) - assert config.prompt_tokens == 65 - assert config.output_tokens == 45 - finally: - Path(config_path).unlink() - - -class TestSyntheticTextItemsGenerator: - """Test cases for SyntheticTextItemsGenerator class. +class TestSyntheticTextGenerator: + """Test cases for SyntheticTextGenerator class. ### WRITTEN BY AI ### """ @@ -360,7 +221,6 @@ def mock_tokenizer(self): ### WRITTEN BY AI ### """ tokenizer = Mock() - tokenizer.get_vocab.return_value = {f"token_{i}": i for i in range(1000)} tokenizer.encode.side_effect = lambda text: list(range(len(text.split()))) tokenizer.decode.side_effect = ( lambda tokens, skip_special_tokens=False: " ".join( @@ -369,23 +229,6 @@ def mock_tokenizer(self): ) return tokenizer - @pytest.fixture - def mock_integer_range_sampler(self): - """Fixture to provide a mocked IntegerRangeSampler. - - ### WRITTEN BY AI ### - """ - with patch("guidellm.dataset.synthetic.IntegerRangeSampler") as mock_sampler: - # Side effect for basic iteration with enough values for larger tests - def mock_sampler_side_effect(*args, **kwargs): - mock_instance = Mock() - # Provide enough values for tests (up to 20 items) - mock_instance.__iter__ = Mock(return_value=iter([15] * 20)) - return mock_instance - - mock_sampler.side_effect = mock_sampler_side_effect - yield mock_sampler - @pytest.fixture def simple_config(self): """Fixture for simple configuration. @@ -395,7 +238,6 @@ def simple_config(self): return SyntheticTextDatasetConfig( prompt_tokens=15, output_tokens=10, - samples=5, source="The quick brown fox jumps over the lazy dog.", ) @@ -413,73 +255,11 @@ def config_with_prefix(self): prefix_buckets=[prefix_bucket], prompt_tokens=15, output_tokens=10, - samples=5, - source="The quick brown fox jumps over the lazy dog.", - ) - - @pytest.fixture - def config_with_multiple_prefix_buckets(self): - """Fixture for configuration with multiple prefix buckets. - - ### WRITTEN BY AI ### - """ - prefix_bucket1 = SyntheticTextPrefixBucketConfig( - bucket_weight=60, prefix_count=1, prefix_tokens=2 - ) - prefix_bucket2 = SyntheticTextPrefixBucketConfig( - bucket_weight=40, prefix_count=1, prefix_tokens=4 - ) - - return SyntheticTextDatasetConfig( - prefix_buckets=[prefix_bucket1, prefix_bucket2], - prompt_tokens=10, - output_tokens=5, - samples=10, - source="The quick brown fox jumps over the lazy dog.", - ) - - @pytest.fixture - def config_with_multiple_prefix_counts(self): - """Fixture for configuration with prefix_count > 1. - - ### WRITTEN BY AI ### - """ - prefix_bucket = SyntheticTextPrefixBucketConfig( - bucket_weight=100, prefix_count=3, prefix_tokens=2 - ) - - return SyntheticTextDatasetConfig( - prefix_buckets=[prefix_bucket], - prompt_tokens=8, - output_tokens=4, - samples=6, - source="The quick brown fox jumps over the lazy dog.", - ) - - @pytest.fixture - def complex_config(self): - """Fixture for complex configuration with variance. - - ### WRITTEN BY AI ### - """ - return SyntheticTextDatasetConfig( - prompt_tokens=20, - prompt_tokens_stdev=5, - prompt_tokens_min=10, - prompt_tokens_max=30, - output_tokens=15, - output_tokens_stdev=3, - output_tokens_min=10, - output_tokens_max=20, - samples=10, source="The quick brown fox jumps over the lazy dog.", ) @pytest.mark.smoke - @patch("guidellm.dataset.synthetic.EndlessTextCreator") - def test_generator_initialization( - self, mock_text_creator, simple_config, mock_tokenizer - ): + def test_generator_initialization(self, simple_config, mock_tokenizer): """Test generator initialization. ### WRITTEN BY AI ### @@ -491,15 +271,9 @@ def test_generator_initialization( assert generator.config == simple_config assert generator.processor == mock_tokenizer assert generator.random_seed == 42 - mock_text_creator.assert_called_once_with(data=simple_config.source) @pytest.mark.smoke - def test_basic_iteration( - self, - mock_integer_range_sampler, - simple_config, - mock_tokenizer, - ): + def test_basic_iteration(self, simple_config, mock_tokenizer): """Test basic iteration functionality. ### WRITTEN BY AI ### @@ -508,16 +282,22 @@ def test_basic_iteration( simple_config, mock_tokenizer, random_seed=42 ) - items = list(generator) + items = [] + for i, item in enumerate(generator): + items.append(item) + if i >= 4: # Only get 5 items + break # Verify we get the expected number of items - assert len(items) == simple_config.samples + assert len(items) == 5 # Verify each item has the required keys for item in items: + assert "prefix" in item assert "prompt" in item assert "prompt_tokens_count" in item assert "output_tokens_count" in item + assert isinstance(item["prefix"], str) assert isinstance(item["prompt"], str) assert isinstance(item["prompt_tokens_count"], int) assert isinstance(item["output_tokens_count"], int) @@ -528,41 +308,26 @@ def test_create_prompt_method(self, simple_config, mock_tokenizer): ### WRITTEN BY AI ### """ + from faker import Faker + generator = SyntheticTextGenerator( simple_config, mock_tokenizer, random_seed=42 ) + faker = Faker() + faker.seed_instance(42) # Test normal case - result = generator._create_prompt(5, 0, 42) - assert result[0] == 42 # Unique prefix token - assert len(result) == 5 + result = generator._create_prompt(5, faker, "unique_prefix ") + assert isinstance(result, str) + # The result should be the decoded tokens (token_0 token_1 etc.) due to our mock + assert "token_" in result # Test zero tokens - result = generator._create_prompt(0, 0, 42) - assert result == [] - - # Test without unique prefix - result = generator._create_prompt(3, 0) - assert len(result) == 3 + result = generator._create_prompt(0, faker) + assert result == "" @pytest.mark.regression - def test_create_prompt_binary_search(self, simple_config, mock_tokenizer): - """Test binary search logic in _create_prompt. - - ### WRITTEN BY AI ### - """ - generator = SyntheticTextGenerator( - simple_config, mock_tokenizer, random_seed=42 - ) - - # Test that binary search finds appropriate length - result = generator._create_prompt(5, 0, 42) - assert len(result) >= 4 # Should include prefix + some tokens - - @pytest.mark.sanity - def test_prefix_tokens_integration( - self, mock_integer_range_sampler, config_with_prefix, mock_tokenizer - ): + def test_prefix_tokens_integration(self, config_with_prefix, mock_tokenizer): """Test integration with prefix tokens. ### WRITTEN BY AI ### @@ -571,19 +336,18 @@ def test_prefix_tokens_integration( config_with_prefix, mock_tokenizer, random_seed=42 ) - items = list(generator) + items = [] + for i, item in enumerate(generator): + items.append(item) + if i >= 2: # Only get 3 items + break - # Verify prompt_tokens_count includes prefix + # Verify prefix is present in items for item in items: - assert ( - item["prompt_tokens_count"] - == config_with_prefix.prefix_buckets[0].prefix_tokens + 15 - ) + assert isinstance(item["prefix"], str) @pytest.mark.regression - def test_random_seeding_consistency( - self, mock_integer_range_sampler, simple_config, mock_tokenizer - ): + def test_random_seeding_consistency(self, simple_config, mock_tokenizer): """Test that same seed produces consistent results. ### WRITTEN BY AI ### @@ -596,426 +360,228 @@ def test_random_seeding_consistency( simple_config, mock_tokenizer, random_seed=42 ) - items1 = list(generator1) - items2 = list(generator2) + items1 = [] + items2 = [] + for i, (item1, item2) in enumerate(zip(generator1, generator2)): + items1.append(item1) + items2.append(item2) + if i >= 2: # Only get 3 items + break # With same seed and deterministic mocks, results should be identical assert len(items1) == len(items2) for item1, item2 in zip(items1, items2): - assert item1["prompt"] == item2["prompt"] assert item1["prompt_tokens_count"] == item2["prompt_tokens_count"] assert item1["output_tokens_count"] == item2["output_tokens_count"] - @pytest.mark.regression - def test_variance_configuration( - self, mock_integer_range_sampler, complex_config, mock_tokenizer - ): - """Test that variance configuration is properly used. - ### WRITTEN BY AI ### - """ - generator = SyntheticTextGenerator( - complex_config, mock_tokenizer, random_seed=42 - ) +class TestSyntheticDatasetDeserializer: + """Test cases for SyntheticDatasetDeserializer class. - # Initialize the generator to trigger sampler creation - generator_iter = iter(generator) - next(generator_iter) - - # Verify that IntegerRangeSampler is called with correct parameters - assert mock_integer_range_sampler.call_count == 2 - - # Check prompt tokens sampler call - prompt_call = mock_integer_range_sampler.call_args_list[0] - assert prompt_call[1]["average"] == complex_config.prompt_tokens - assert prompt_call[1]["variance"] == complex_config.prompt_tokens_stdev - assert prompt_call[1]["min_value"] == complex_config.prompt_tokens_min - assert prompt_call[1]["max_value"] == complex_config.prompt_tokens_max - assert prompt_call[1]["random_seed"] == 42 - - # Check output tokens sampler call - output_call = mock_integer_range_sampler.call_args_list[1] - assert output_call[1]["average"] == complex_config.output_tokens - assert output_call[1]["variance"] == complex_config.output_tokens_stdev - assert output_call[1]["min_value"] == complex_config.output_tokens_min - assert output_call[1]["max_value"] == complex_config.output_tokens_max - assert output_call[1]["random_seed"] == 43 # 42 + 1 + ### WRITTEN BY AI ### + """ - @pytest.mark.regression - def test_unique_prefix_generation(self, simple_config, mock_tokenizer): - """Test that unique prefixes are generated for each request. + @pytest.fixture + def mock_tokenizer(self): + """Fixture to provide a mocked tokenizer. ### WRITTEN BY AI ### """ - # Mock the cycle to return predictable values - with patch("guidellm.dataset.synthetic.cycle") as mock_cycle: - mock_cycle.return_value = iter([100, 101, 102, 103, 104]) - - generator = SyntheticTextGenerator( - simple_config, mock_tokenizer, random_seed=42 + tokenizer = Mock() + tokenizer.encode.side_effect = lambda text: list(range(len(text.split()))) + tokenizer.decode.side_effect = ( + lambda tokens, skip_special_tokens=False: " ".join( + f"token_{t}" for t in tokens[:5] ) - - # Access the iterator to trigger the cycle creation - generator_iter = iter(generator) - next(generator_iter) - - # Verify cycle was called with vocab values - mock_cycle.assert_called_once() - - @pytest.mark.regression - def test_multiple_prefix_buckets_distribution( - self, - mock_integer_range_sampler, - config_with_multiple_prefix_buckets, - mock_tokenizer, - ): - """Test distribution across multiple prefix buckets with different weights. - - ### WRITTEN BY AI ### - """ - generator = SyntheticTextGenerator( - config_with_multiple_prefix_buckets, mock_tokenizer, random_seed=42 ) - - items = list(generator) - - # Verify we get the expected number of items - assert len(items) == config_with_multiple_prefix_buckets.samples - - # Verify that prefix tokens are added to prompt_tokens_count - # Since we have buckets with 2 and 4 prefix tokens, and the mock returns 15 - # prompt tokens, we should see prompt_tokens_count of either 17 or 19 - prefix_counts = [item["prompt_tokens_count"] for item in items] - assert all(count in [17, 19] for count in prefix_counts) - - # Calculate expected distribution based on weights - # Bucket 1: weight=60, prefix_count=1, prefix_tokens=2 - # Bucket 2: weight=40, prefix_count=1, prefix_tokens=4 - # Total weight = 100, samples = 10 - # Bucket 1: (60/1/100) * 10 = 6 samples with 17 tokens (2 prefix + 15 prompt) - # Bucket 2: (40/1/100) * 10 = 4 samples with 19 tokens (4 prefix + 15 prompt) - count_17 = prefix_counts.count(17) # 2 prefix tokens - count_19 = prefix_counts.count(19) # 4 prefix tokens - assert count_17 == 6 - assert count_19 == 4 - - @pytest.mark.regression - def test_multiple_prefix_counts( - self, - mock_integer_range_sampler, - config_with_multiple_prefix_counts, - mock_tokenizer, - ): - """Test prefix buckets with prefix_count > 1. - - ### WRITTEN BY AI ### - """ - generator = SyntheticTextGenerator( - config_with_multiple_prefix_counts, mock_tokenizer, random_seed=42 - ) - - items = list(generator) - - # Verify we get the expected number of items - assert len(items) == config_with_multiple_prefix_counts.samples - - # All items should have 2 prefix tokens + 15 prompt tokens = 17 total - for item in items: - assert item["prompt_tokens_count"] == 17 + return tokenizer @pytest.mark.sanity - def test_prefix_buckets_create_prefixes_method( - self, config_with_multiple_prefix_buckets, mock_tokenizer - ): - """Test the _create_prefixes method directly. + def test_load_config_file_yaml(self): + """Test loading YAML config file. ### WRITTEN BY AI ### """ - generator = SyntheticTextGenerator( - config_with_multiple_prefix_buckets, mock_tokenizer, random_seed=42 - ) - - # Test _create_prefixes method - rand = Mock() - rand.randint = Mock(return_value=0) - prefixes = generator._create_prefixes(rand) - - # Should return a sequence of prefix token lists - assert isinstance(prefixes, list) - assert len(prefixes) == 10 - - # Each prefix should be a list of integers - for prefix in prefixes: - assert isinstance(prefix, list) - assert all(isinstance(token, int) for token in prefix) - - @pytest.mark.regression - def test_empty_prefix_buckets( - self, mock_integer_range_sampler, simple_config, mock_tokenizer - ): - """Test behavior when prefix_buckets is None or empty. - - ### WRITTEN BY AI ### - """ - # Test with None prefix_buckets (simple_config has None) - generator = SyntheticTextGenerator( - simple_config, mock_tokenizer, random_seed=42 - ) - - items = list(generator) - - # All items should have exactly the prompt tokens (no prefix) - for item in items: - assert item["prompt_tokens_count"] == 15 # Mock returns 15 - - -class TestSyntheticDatasetCreator: - """Test cases for SyntheticDatasetCreator class. - - ### WRITTEN BY AI ### - """ - - @pytest.mark.sanity - def test_is_supported_path_config_file(self): - """Test is_supported with config file paths. + config_data = { + "prompt_tokens": 60, + "output_tokens": 15, + "source": "yaml_test.txt", + "prefix_buckets": [ + {"bucket_weight": 100, "prefix_count": 1, "prefix_tokens": 3} + ], + } - ### WRITTEN BY AI ### - """ - with tempfile.NamedTemporaryFile(suffix=".config", delete=False) as f: - config_path = Path(f.name) + with tempfile.NamedTemporaryFile(mode="w", suffix=".yaml", delete=False) as f: + yaml.dump(config_data, f) + yaml_path = f.name try: - assert SyntheticTextDatasetDeserializer.is_supported(config_path, None) + deserializer = SyntheticTextDatasetDeserializer() + config = deserializer._load_config_file(yaml_path) + + assert config.prompt_tokens == 60 + assert config.output_tokens == 15 + assert config.source == "yaml_test.txt" + assert config.prefix_buckets[0].prefix_tokens == 3 # type: ignore [index] finally: - config_path.unlink() + Path(yaml_path).unlink() @pytest.mark.sanity - def test_is_supported_path_yaml_file(self): - """Test is_supported with YAML file paths. + def test_load_config_file_config_extension(self): + """Test loading .config file. ### WRITTEN BY AI ### """ - with tempfile.NamedTemporaryFile(suffix=".yaml", delete=False) as f: - yaml_path = Path(f.name) + config_data = { + "prompt_tokens": 90, + "output_tokens": 35, + "prefix_buckets": [ + {"bucket_weight": 100, "prefix_count": 1, "prefix_tokens": 2} + ], + } + + with tempfile.NamedTemporaryFile(mode="w", suffix=".config", delete=False) as f: + yaml.dump(config_data, f) + config_path = f.name try: - assert SyntheticTextDatasetDeserializer.is_supported(yaml_path, None) + deserializer = SyntheticTextDatasetDeserializer() + config = deserializer._load_config_file(config_path) + + assert config.prompt_tokens == 90 + assert config.output_tokens == 35 + assert config.prefix_buckets[0].prefix_tokens == 2 # type: ignore [index] finally: - yaml_path.unlink() + Path(config_path).unlink() @pytest.mark.smoke - def test_is_supported_json_string(self): - """Test is_supported with JSON string. + def test_load_config_str_json(self): + """Test loading JSON string config. ### WRITTEN BY AI ### """ json_str = '{"prompt_tokens": 50, "output_tokens": 25}' - assert SyntheticTextDatasetDeserializer.is_supported(json_str, None) + deserializer = SyntheticTextDatasetDeserializer() + config = deserializer._load_config_str(json_str) + + assert config.prompt_tokens == 50 + assert config.output_tokens == 25 @pytest.mark.smoke - def test_is_supported_key_value_string(self): - """Test is_supported with key-value string. + def test_load_config_str_key_value(self): + """Test loading key-value string config. ### WRITTEN BY AI ### """ kv_str = "prompt_tokens=50,output_tokens=25" - assert SyntheticTextDatasetDeserializer.is_supported(kv_str, None) - - @pytest.mark.sanity - def test_is_supported_config_filename_string(self): - """Test is_supported with config filename string. + deserializer = SyntheticTextDatasetDeserializer() + config = deserializer._load_config_str(kv_str) - ### WRITTEN BY AI ### - """ - assert SyntheticTextDatasetDeserializer.is_supported("config.yaml", None) - assert SyntheticTextDatasetDeserializer.is_supported("settings.config", None) + assert config.prompt_tokens == 50 + assert config.output_tokens == 25 @pytest.mark.sanity - def test_is_not_supported_regular_string(self): - """Test is_supported returns False for regular strings. + def test_load_config_str_invalid_format(self): + """Test loading invalid format raises DataNotSupportedError. ### WRITTEN BY AI ### """ - assert not SyntheticTextDatasetDeserializer.is_supported("regular string", None) - assert not SyntheticTextDatasetDeserializer.is_supported("single=pair", None) + deserializer = SyntheticTextDatasetDeserializer() + with pytest.raises(DataNotSupportedError, match="Unsupported string data"): + deserializer._load_config_str("invalid_format_string") @pytest.mark.regression - def test_is_not_supported_non_existent_path(self): - """Test is_supported returns False for non-existent paths. + def test_load_config_file_non_existent(self): + """Test loading non-existent file returns None. ### WRITTEN BY AI ### """ - non_existent_path = Path("/non/existent/path.config") - assert not SyntheticTextDatasetDeserializer.is_supported(non_existent_path, None) + deserializer = SyntheticTextDatasetDeserializer() + config = deserializer._load_config_file("/non/existent/path.config") + assert config is None @pytest.mark.regression - def test_is_not_supported_other_types(self): - """Test is_supported returns False for other data types. + def test_load_config_str_non_string(self): + """Test loading non-string returns None. ### WRITTEN BY AI ### """ - assert not SyntheticTextDatasetDeserializer.is_supported(123, None) - assert not SyntheticTextDatasetDeserializer.is_supported(["list"], None) - assert not SyntheticTextDatasetDeserializer.is_supported({"dict": "value"}, None) + deserializer = SyntheticTextDatasetDeserializer() + config = deserializer._load_config_str(123) + assert config is None @pytest.mark.smoke - @patch("guidellm.dataset.synthetic.check_load_processor") - @patch("guidellm.dataset.synthetic.SyntheticTextItemsGenerator") - @patch("guidellm.dataset.synthetic.Dataset") - def test_handle_create_basic( - self, mock_dataset, mock_generator, mock_check_processor - ): - """Test handle_create basic functionality. + def test_call_with_config_object(self, mock_tokenizer): + """Test calling deserializer with SyntheticTextDatasetConfig. ### WRITTEN BY AI ### """ - # Setup mocks - mock_processor = Mock() - mock_check_processor.return_value = mock_processor - - mock_generator_instance = Mock() - mock_generator_instance.__iter__ = Mock( - return_value=iter( - [ - { - "prompt": "test", - "prompt_tokens_count": 10, - "output_tokens_count": 5, - } - ] - ) - ) - mock_generator.return_value = mock_generator_instance - - mock_dataset_instance = Mock() - mock_dataset.from_list.return_value = mock_dataset_instance - - # Test - data = '{"prompt_tokens": 50, "output_tokens": 25}' - result = SyntheticTextDatasetDeserializer.handle_create( - data=data, - data_args=None, - processor="gpt2", - processor_args=None, + config = SyntheticTextDatasetConfig(prompt_tokens=50, output_tokens=25) + deserializer = SyntheticTextDatasetDeserializer() + + result = deserializer( + data=config, + data_kwargs={}, + processor_factory=lambda: mock_tokenizer, random_seed=42, ) - # Verify - mock_check_processor.assert_called_once_with( - "gpt2", - None, - error_msg="Processor/tokenizer required for synthetic dataset generation.", - ) - mock_generator.assert_called_once() - mock_dataset.from_list.assert_called_once() - assert result == mock_dataset_instance + assert isinstance(result, IterableDataset) - @pytest.mark.sanity - @patch("guidellm.dataset.synthetic.check_load_processor") - def test_handle_create_processor_required(self, mock_check_processor): - """Test handle_create requires processor. + @pytest.mark.regression + def test_call_with_unsupported_data(self, mock_tokenizer): + """Test calling deserializer with unsupported data raises error. ### WRITTEN BY AI ### """ - mock_check_processor.side_effect = ValueError("Processor required") - - data = '{"prompt_tokens": 50, "output_tokens": 25}' + deserializer = SyntheticTextDatasetDeserializer() - with pytest.raises(ValueError, match="Processor required"): - SyntheticTextDatasetDeserializer.handle_create( - data=data, - data_args=None, - processor=None, - processor_args=None, + with pytest.raises(DataNotSupportedError, match="Unsupported data"): + deserializer( + data=123, + data_kwargs={}, + processor_factory=lambda: mock_tokenizer, random_seed=42, ) @pytest.mark.regression - @patch("guidellm.dataset.synthetic.check_load_processor") - @patch("guidellm.dataset.synthetic.SyntheticTextItemsGenerator") - @patch("guidellm.dataset.synthetic.Dataset") - def test_handle_create_with_data_args( - self, mock_dataset, mock_generator, mock_check_processor - ): - """Test handle_create with data_args. + def test_call_with_json_string(self, mock_tokenizer): + """Test calling deserializer with JSON string. ### WRITTEN BY AI ### """ - # Setup mocks - mock_processor = Mock() - mock_check_processor.return_value = mock_processor - - mock_generator_instance = Mock() - mock_generator_instance.__iter__ = Mock(return_value=iter([])) - mock_generator.return_value = mock_generator_instance - - mock_dataset_instance = Mock() - mock_dataset.from_list.return_value = mock_dataset_instance - - # Test with data_args - data = '{"prompt_tokens": 50, "output_tokens": 25}' - data_args = {"features": "custom_features"} - - SyntheticTextDatasetDeserializer.handle_create( - data=data, - data_args=data_args, - processor="gpt2", - processor_args=None, + json_str = '{"prompt_tokens": 50, "output_tokens": 25}' + deserializer = SyntheticTextDatasetDeserializer() + + result = deserializer( + data=json_str, + data_kwargs={}, + processor_factory=lambda: mock_tokenizer, random_seed=42, ) - # Verify data_args are passed to Dataset.from_list - mock_dataset.from_list.assert_called_once_with([], **data_args) - - @pytest.mark.sanity - def test_extract_args_column_mappings_empty(self): - """Test extract_args_column_mappings with empty data_args. - - ### WRITTEN BY AI ### - """ - result = SyntheticTextDatasetDeserializer.extract_args_column_mappings(None) - - expected = { - "prompt_column": "prompt", - "prompt_tokens_count_column": "prompt_tokens_count", - "output_tokens_count_column": "output_tokens_count", - } - assert result == expected + assert isinstance(result, IterableDataset) @pytest.mark.regression - def test_extract_args_column_mappings_with_parent_mappings(self): - """Test extract_args_column_mappings rejects column mappings. + def test_call_with_config_file(self, mock_tokenizer): + """Test calling deserializer with config file. ### WRITTEN BY AI ### """ - with ( - patch.object( - SyntheticTextDatasetDeserializer.__bases__[0], - "extract_args_column_mappings", - return_value={"prompt_column": "custom_prompt"}, - ), - pytest.raises(ValueError, match="Column mappings are not supported"), - ): - SyntheticTextDatasetDeserializer.extract_args_column_mappings({"some": "args"}) + config_data = {"prompt_tokens": 65, "output_tokens": 45} - @pytest.mark.regression - def test_extract_args_column_mappings_no_parent_mappings(self): - """Test extract_args_column_mappings with no parent mappings. + with tempfile.NamedTemporaryFile(mode="w", suffix=".yaml", delete=False) as f: + yaml.dump(config_data, f) + config_path = f.name - ### WRITTEN BY AI ### - """ - with patch.object( - SyntheticTextDatasetDeserializer.__bases__[0], - "extract_args_column_mappings", - return_value={}, - ): - result = SyntheticTextDatasetDeserializer.extract_args_column_mappings( - {"some": "args"} + try: + deserializer = SyntheticTextDatasetDeserializer() + result = deserializer( + data=config_path, + data_kwargs={}, + processor_factory=lambda: mock_tokenizer, + random_seed=42, ) - - expected = { - "prompt_column": "prompt", - "prompt_tokens_count_column": "prompt_tokens_count", - "output_tokens_count_column": "output_tokens_count", - } - assert result == expected + assert isinstance(result, IterableDataset) + finally: + Path(config_path).unlink()