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manuelcandalesmanuelcandales
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Add half_precision condition to TensorConfig and refactor specdb tests
ghstack-source-id: 2a8d22a Pull-Request: #38
1 parent aedd5b1 commit a80a15b

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3 files changed

+65
-44
lines changed

3 files changed

+65
-44
lines changed

‎facto/inputgen/utils/config.py

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Original file line numberDiff line numberDiff line change
@@ -6,13 +6,16 @@
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from enum import Enum
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import torch
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class Condition(str, Enum):
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ALLOW_EMPTY = "empty"
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ALLOW_TRANSPOSED = "transposed"
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ALLOW_PERMUTED = "permuted"
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ALLOW_STRIDED = "strided"
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DISALLOW_DTYPES = "disallow_dtypes"
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HALF_PRECISION = "half_precision"
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class TensorConfig:
@@ -23,6 +26,8 @@ def __init__(self, device="cpu", disallow_dtypes=None, **conditions):
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for condition, value in conditions.items():
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if condition in self.conditions:
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self.conditions[condition] = value
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if self.conditions[Condition.HALF_PRECISION] is False:
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self.disallow_dtypes += [torch.float16, torch.bfloat16]
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self.probability = 0.5
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def is_allowed(self, condition: Condition) -> bool:

‎test/specdb/test_specdb_cpu.py

Lines changed: 16 additions & 9 deletions
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@@ -7,26 +7,33 @@
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import unittest
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from base_test import BaseSpecDBTest
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from facto.inputgen.utils.config import TensorConfig
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class TestSpecDBOperationsCPU(BaseSpecDBTest):
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"""Test class for validating all specs in SpecDB using gen_errors on CPU."""
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SKIP_OPS = [
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"_native_batch_norm_legit_no_training.default",
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"addmm.default",
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"arange.default",
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"arange.start_step",
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"constant_pad_nd.default",
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"split_with_sizes_copy.default",
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]
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def test_all_ops_cpu(self):
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skip_ops = [
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"_native_batch_norm_legit_no_training.default",
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"addmm.default",
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"arange.default",
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"arange.start_step",
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"constant_pad_nd.default",
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"split_with_sizes_copy.default",
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]
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config = TensorConfig(device="cpu", half_precision=False)
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self._run_all_ops(config=config, skip_ops=self.SKIP_OPS)
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def test_all_ops_cpu_half(self):
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skip_ops = self.SKIP_OPS.copy()
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# "cdist" not implemented for 'Half' on CPU
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# "pdist" not implemented for 'Half' on CPU
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skip_ops += ["_cdist_forward.default", "_pdist_forward.default"]
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self._run_all_ops(skip_ops=skip_ops)
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config = TensorConfig(device="cpu", half_precision=True)
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self._run_all_ops(config=config, skip_ops=skip_ops)
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if __name__ == "__main__":

‎test/specdb/test_specdb_mps.py

Lines changed: 44 additions & 35 deletions
Original file line numberDiff line numberDiff line change
@@ -15,46 +15,55 @@
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class TestSpecDBOperationsMPS(BaseSpecDBTest):
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"""Test class for validating all specs in SpecDB using gen_errors on MPS."""
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SKIP_OPS = [
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# Calibrate specs (cpu not passing either):
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"addmm.default",
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"arange.default",
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"arange.start_step",
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"constant_pad_nd.default",
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"split_with_sizes_copy.default",
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# https://github.com/pytorch/pytorch/issues/160208
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"add.Tensor",
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"add.Scalar",
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"rsub.Scalar",
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"sub.Tensor",
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"sub.Scalar",
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# crash: https://github.com/pytorch/pytorch/issues/154887
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"_native_batch_norm_legit_no_training.default",
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# not implemented
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"_pdist_forward.default",
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# impl: clamp tensor number of dims must not be greater than that of input tensor
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"clamp.Tensor",
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# crash: https://github.com/pytorch/pytorch/issues/154881
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"cumsum.default",
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# sparse_grad not supported in MPS yet
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"gather.default",
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# Dimension specified as -1 but tensor has no dimensions
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"index_select.default",
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# crash: https://github.com/pytorch/pytorch/issues/154882
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"max_pool2d_with_indices.default",
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# On-going issue on MPSGraph topk when ndims() - axis > 4, see issue #154890
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# https://github.com/pytorch/pytorch/issues/154890
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"topk.default",
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# var_mps: reduction dim must be in the range of input shape
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"var.correction",
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"var.dim",
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]
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def test_all_ops_mps(self):
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skip_ops = [
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# Calibrate specs (cpu not passing either):
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"addmm.default",
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"arange.default",
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"arange.start_step",
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"constant_pad_nd.default",
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"split_with_sizes_copy.default",
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# https://github.com/pytorch/pytorch/issues/160208
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"add.Tensor",
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"add.Scalar",
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"rsub.Scalar",
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"sub.Tensor",
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"sub.Scalar",
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# crash: https://github.com/pytorch/pytorch/issues/154887
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"_native_batch_norm_legit_no_training.default",
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# not implemented
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"_pdist_forward.default",
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# impl: clamp tensor number of dims must not be greater than that of input tensor
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"clamp.Tensor",
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# crash: https://github.com/pytorch/pytorch/issues/154881
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"cumsum.default",
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# sparse_grad not supported in MPS yet
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"gather.default",
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# Dimension specified as -1 but tensor has no dimensions
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"index_select.default",
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# crash: https://github.com/pytorch/pytorch/issues/154882
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"max_pool2d_with_indices.default",
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# On-going issue on MPSGraph topk when ndims() - axis > 4, see issue #154890
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# https://github.com/pytorch/pytorch/issues/154890
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"topk.default",
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# var_mps: reduction dim must be in the range of input shape
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"var.correction",
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"var.dim",
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]
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config = TensorConfig(
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device="mps", disallow_dtypes=[torch.float64], half_precision=False
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)
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self._run_all_ops(config=config, skip_ops=self.SKIP_OPS)
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def test_all_ops_mps_half(self):
60+
skip_ops = self.SKIP_OPS.copy()
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# ConvTranspose 3D with BF16 or FP16 types is not supported on MPS
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skip_ops += ["convolution.default"]
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config = TensorConfig(device="mps", disallow_dtypes=[torch.float64])
64+
config = TensorConfig(
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device="mps", disallow_dtypes=[torch.float64], half_precision=True
66+
)
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self._run_all_ops(config=config, skip_ops=skip_ops)
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