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Add half_precision condition to TensorConfig and refactor specdb tests #38

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Add half_precision condition to TensorConfig and refactor specdb tests #38

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manuelcandales Aug 18, 2025
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manuelcandales Aug 18, 2025
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5 changes: 5 additions & 0 deletions facto/inputgen/utils/config.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,13 +6,16 @@

from enum import Enum

import torch


class Condition(str, Enum):
ALLOW_EMPTY = "empty"
ALLOW_TRANSPOSED = "transposed"
ALLOW_PERMUTED = "permuted"
ALLOW_STRIDED = "strided"
DISALLOW_DTYPES = "disallow_dtypes"
HALF_PRECISION = "half_precision"


class TensorConfig:
Expand All @@ -23,6 +26,8 @@ def __init__(self, device="cpu", disallow_dtypes=None, **conditions):
for condition, value in conditions.items():
if condition in self.conditions:
self.conditions[condition] = value
if self.conditions[Condition.HALF_PRECISION] is False:
self.disallow_dtypes += [torch.float16, torch.bfloat16]
self.probability = 0.5

def is_allowed(self, condition: Condition) -> bool:
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25 changes: 16 additions & 9 deletions test/specdb/test_specdb_cpu.py
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Expand Up @@ -7,26 +7,33 @@
import unittest

from base_test import BaseSpecDBTest
from facto.inputgen.utils.config import TensorConfig


class TestSpecDBOperationsCPU(BaseSpecDBTest):
"""Test class for validating all specs in SpecDB using gen_errors on CPU."""

SKIP_OPS = [
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all after including HALF_PRECISION?

"_native_batch_norm_legit_no_training.default",
"addmm.default",
"arange.default",
"arange.start_step",
"constant_pad_nd.default",
"split_with_sizes_copy.default",
]

def test_all_ops_cpu(self):
skip_ops = [
"_native_batch_norm_legit_no_training.default",
"addmm.default",
"arange.default",
"arange.start_step",
"constant_pad_nd.default",
"split_with_sizes_copy.default",
]
config = TensorConfig(device="cpu", half_precision=False)
self._run_all_ops(config=config, skip_ops=self.SKIP_OPS)

def test_all_ops_cpu_half(self):
skip_ops = self.SKIP_OPS.copy()
# "cdist" not implemented for 'Half' on CPU
# "pdist" not implemented for 'Half' on CPU
skip_ops += ["_cdist_forward.default", "_pdist_forward.default"]

self._run_all_ops(skip_ops=skip_ops)
config = TensorConfig(device="cpu", half_precision=True)
self._run_all_ops(config=config, skip_ops=skip_ops)


if __name__ == "__main__":
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79 changes: 44 additions & 35 deletions test/specdb/test_specdb_mps.py
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Expand Up @@ -15,46 +15,55 @@
class TestSpecDBOperationsMPS(BaseSpecDBTest):
"""Test class for validating all specs in SpecDB using gen_errors on MPS."""

SKIP_OPS = [
# Calibrate specs (cpu not passing either):
"addmm.default",
"arange.default",
"arange.start_step",
"constant_pad_nd.default",
"split_with_sizes_copy.default",
# https://github.com/pytorch/pytorch/issues/160208
"add.Tensor",
"add.Scalar",
"rsub.Scalar",
"sub.Tensor",
"sub.Scalar",
# crash: https://github.com/pytorch/pytorch/issues/154887
"_native_batch_norm_legit_no_training.default",
# not implemented
"_pdist_forward.default",
# impl: clamp tensor number of dims must not be greater than that of input tensor
"clamp.Tensor",
# crash: https://github.com/pytorch/pytorch/issues/154881
"cumsum.default",
# sparse_grad not supported in MPS yet
"gather.default",
# Dimension specified as -1 but tensor has no dimensions
"index_select.default",
# crash: https://github.com/pytorch/pytorch/issues/154882
"max_pool2d_with_indices.default",
# On-going issue on MPSGraph topk when ndims() - axis > 4, see issue #154890
# https://github.com/pytorch/pytorch/issues/154890
"topk.default",
# var_mps: reduction dim must be in the range of input shape
"var.correction",
"var.dim",
]

def test_all_ops_mps(self):
skip_ops = [
# Calibrate specs (cpu not passing either):
"addmm.default",
"arange.default",
"arange.start_step",
"constant_pad_nd.default",
"split_with_sizes_copy.default",
# https://github.com/pytorch/pytorch/issues/160208
"add.Tensor",
"add.Scalar",
"rsub.Scalar",
"sub.Tensor",
"sub.Scalar",
# crash: https://github.com/pytorch/pytorch/issues/154887
"_native_batch_norm_legit_no_training.default",
# not implemented
"_pdist_forward.default",
# impl: clamp tensor number of dims must not be greater than that of input tensor
"clamp.Tensor",
# crash: https://github.com/pytorch/pytorch/issues/154881
"cumsum.default",
# sparse_grad not supported in MPS yet
"gather.default",
# Dimension specified as -1 but tensor has no dimensions
"index_select.default",
# crash: https://github.com/pytorch/pytorch/issues/154882
"max_pool2d_with_indices.default",
# On-going issue on MPSGraph topk when ndims() - axis > 4, see issue #154890
# https://github.com/pytorch/pytorch/issues/154890
"topk.default",
# var_mps: reduction dim must be in the range of input shape
"var.correction",
"var.dim",
]
config = TensorConfig(
device="mps", disallow_dtypes=[torch.float64], half_precision=False
)
self._run_all_ops(config=config, skip_ops=self.SKIP_OPS)

def test_all_ops_mps_half(self):
skip_ops = self.SKIP_OPS.copy()
# ConvTranspose 3D with BF16 or FP16 types is not supported on MPS
skip_ops += ["convolution.default"]

config = TensorConfig(device="mps", disallow_dtypes=[torch.float64])
config = TensorConfig(
device="mps", disallow_dtypes=[torch.float64], half_precision=True
)
self._run_all_ops(config=config, skip_ops=skip_ops)


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