repo stringlengths 1 99 | file stringlengths 13 215 | code stringlengths 12 59.2M | file_length int64 12 59.2M | avg_line_length float64 3.82 1.48M | max_line_length int64 12 2.51M | extension_type stringclasses 1
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pytorch | pytorch-main/test/jit/test_module_containers.py | # Owner(s): ["oncall: jit"]
import os
import sys
from typing import Any, List, Tuple
from collections import OrderedDict
import torch
import torch.nn as nn
from torch.testing._internal.jit_utils import JitTestCase
# Make the helper files in test/ importable
pytorch_test_dir = os.path.dirname(os.path.dirname(os.path.... | 25,072 | 35.024425 | 127 | py |
pytorch | pytorch-main/test/jit/test_tensor_creation_ops.py | # Owner(s): ["oncall: jit"]
import os
import sys
import torch
# Make the helper files in test/ importable
pytorch_test_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
sys.path.append(pytorch_test_dir)
from torch.testing._internal.jit_utils import JitTestCase
if __name__ == '__main__':
raise R... | 2,993 | 38.394737 | 81 | py |
pytorch | pytorch-main/test/jit/test_dataclasses.py | # Owner(s): ["oncall: jit"]
# flake8: noqa
from dataclasses import dataclass, field, InitVar
from hypothesis import given, settings, strategies as st
from torch.testing._internal.jit_utils import JitTestCase
from typing import List, Optional
import sys
import torch
import unittest
from enum import Enum
# Example jitt... | 4,484 | 26.181818 | 122 | py |
pytorch | pytorch-main/test/jit/test_ignore_context_manager.py | # Owner(s): ["oncall: jit"]
import os
import sys
import unittest
import torch
# Make the helper files in test/ importable
pytorch_test_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
sys.path.append(pytorch_test_dir)
from torch.testing._internal.jit_utils import JitTestCase
from torch.jit.frontend... | 3,324 | 35.141304 | 105 | py |
pytorch | pytorch-main/test/jit/test_data_parallel.py | # Owner(s): ["oncall: jit"]
import os
import sys
import unittest
import torch
import torch.nn as nn
import torch.nn.parallel as dp
# Make the helper files in test/ importable
pytorch_test_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
sys.path.append(pytorch_test_dir)
from torch.testing._internal... | 5,731 | 35.74359 | 81 | py |
pytorch | pytorch-main/test/jit/test_remove_mutation.py | # Owner(s): ["oncall: jit"]
import os
import sys
import torch
from torch.testing import FileCheck
from typing import List
# Make the helper files in test/ importable
pytorch_test_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
sys.path.append(pytorch_test_dir)
from torch.testing._internal.jit_util... | 10,439 | 32.461538 | 92 | py |
pytorch | pytorch-main/test/jit/test_typing.py | # Owner(s): ["oncall: jit"]
import os
import sys
import torch
from torch.testing._internal.jit_utils import JitTestCase, make_global
from torch.testing._internal.common_utils import IS_WINDOWS
from collections import namedtuple
from typing import List, Tuple, Dict, NamedTuple
# Make the helper files in test/ importa... | 21,036 | 31.666149 | 123 | py |
pytorch | pytorch-main/test/jit/test_device_analysis.py | # Owner(s): ["oncall: jit"]
from itertools import product
import unittest
import torch
from torch.testing._internal.common_utils import TEST_CUDA
from torch.testing._internal.jit_utils import JitTestCase
from torch.jit._passes._property_propagation import apply_input_props_using_example
try:
from torchvision imp... | 11,567 | 33.224852 | 92 | py |
pytorch | pytorch-main/test/jit/test_sparse.py | # Owner(s): ["oncall: jit"]
import io
import torch
import unittest
from torch.testing._internal.common_utils import IS_WINDOWS, TEST_MKL
from torch.testing._internal.jit_utils import JitTestCase
class TestSparse(JitTestCase):
def test_freeze_sparse_coo(self):
class SparseTensorModule(torch.nn.Module):
... | 3,696 | 29.303279 | 78 | py |
pytorch | pytorch-main/test/jit/test_recursive_script.py | # Owner(s): ["oncall: jit"]
import os
import sys
import types
import typing
import typing_extensions
from typing import List, Dict, Optional, Tuple
import torch
import torch.nn as nn
from torch import Tensor
from torch.testing import FileCheck
from collections import OrderedDict
# Make the helper files in test/ impo... | 21,776 | 28.349057 | 128 | py |
pytorch | pytorch-main/test/jit/test_ignorable_args.py | # Owner(s): ["oncall: jit"]
import os
import sys
import torch
from torch._C import parse_ir
from torch.testing import FileCheck
# Make the helper files in test/ importable
pytorch_test_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
sys.path.append(pytorch_test_dir)
from torch.testing._internal.jit... | 2,371 | 42.127273 | 98 | py |
pytorch | pytorch-main/test/jit/test_union.py | # Owner(s): ["oncall: jit"]
import io
import os
import sys
import torch
from torch.testing import FileCheck
from enum import Enum
from textwrap import dedent
from typing import Dict, List, Optional, Tuple, Union
# Make the helper files in test/ importable
pytorch_test_dir = os.path.dirname(os.path.dirname(os.path.re... | 35,963 | 34.607921 | 99 | py |
pytorch | pytorch-main/test/jit/test_module_apis.py | # Owner(s): ["oncall: jit"]
import torch
import os
import sys
from torch.testing._internal.jit_utils import JitTestCase
from typing import Dict, Any, List
# Make the helper files in test/ importable
pytorch_test_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
sys.path.append(pytorch_test_dir)
if _... | 5,202 | 39.333333 | 82 | py |
pytorch | pytorch-main/test/jit/test_hooks_modules.py | # Owner(s): ["oncall: jit"]
import torch
from typing import List, Tuple
class SubmoduleNoForwardInputs(torch.nn.Module):
def __init__(self, name):
super().__init__()
self.name = name
def forward(self):
assert self.name == "inner_mod_name"
class ModuleNoForwardInputs(torch.nn.Module... | 18,131 | 33.211321 | 88 | py |
pytorch | pytorch-main/test/jit/test_hash.py | # Owner(s): ["oncall: jit"]
import os
import sys
import torch
from typing import Tuple, List
# Make the helper files in test/ importable
pytorch_test_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
sys.path.append(pytorch_test_dir)
from torch.testing._internal.jit_utils import JitTestCase
if __n... | 3,797 | 32.610619 | 114 | py |
pytorch | pytorch-main/test/jit/test_exception.py | # Owner(s): ["oncall: jit"]
from torch.testing._internal.common_utils import TestCase
import torch
from torch import nn
r"""
Test TorchScript exception handling.
"""
class TestException(TestCase):
def test_pyop_exception_message(self):
class Foo(torch.jit.ScriptModule):
def __init__(self):
... | 5,567 | 30.636364 | 117 | py |
pytorch | pytorch-main/test/jit/test_script_profile.py | # Owner(s): ["oncall: jit"]
import os
import sys
import torch
from torch import nn
# Make the helper files in test/ importable
pytorch_test_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
sys.path.append(pytorch_test_dir)
from torch.testing._internal.jit_utils import JitTestCase
if __name__ == '_... | 3,111 | 26.785714 | 81 | py |
pytorch | pytorch-main/test/jit/test_unsupported_ops.py | # Owner(s): ["oncall: jit"]
import os
import sys
import torch
import unittest
# Make the helper files in test/ importable
pytorch_test_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
sys.path.append(pytorch_test_dir)
from torch.testing._internal.jit_utils import JitTestCase
if __name__ == '__main... | 3,097 | 37.246914 | 90 | py |
pytorch | pytorch-main/test/jit/test_enum.py | # Owner(s): ["oncall: jit"]
import os
import sys
import torch
from torch.testing import FileCheck
from enum import Enum
from typing import Any, List
# Make the helper files in test/ importable
pytorch_test_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
sys.path.append(pytorch_test_dir)
from torch... | 10,170 | 26.865753 | 114 | py |
pytorch | pytorch-main/test/jit/test_await.py | # Owner(s): ["oncall: jit"]
import io
import torch
from torch.testing._internal.jit_utils import JitTestCase
from torch.testing._internal.jit_utils import make_global
from typing import List, Optional, Tuple
from torch import Tensor
from torch._awaits import _Await as Await
class TestAwait(JitTestCase):
def test... | 12,016 | 30.05168 | 96 | py |
pytorch | pytorch-main/test/jit/test_peephole.py | # Owner(s): ["oncall: jit"]
import torch
from torch.testing._internal.jit_utils import JitTestCase, RUN_CUDA, _inline_everything
from torch import nn
from torch.testing import FileCheck
from typing import Callable, List
import unittest
if __name__ == '__main__':
raise RuntimeError("This test file is not meant to... | 29,562 | 32.518141 | 92 | py |
pytorch | pytorch-main/test/jit/test_aten_pow.py | # Owner(s): ["oncall: jit"]
import torch
from torch.testing._internal.common_utils import TestCase
class TestAtenPow(TestCase):
def test_aten_pow_zero_negative_exponent(self):
'''
1. Testing a = int, b = int
'''
@torch.jit.script
def fn_int_int(a: int, b: int):
... | 4,381 | 46.11828 | 79 | py |
pytorch | pytorch-main/test/jit/test_attr.py | # Owner(s): ["oncall: jit"]
from torch.testing import FileCheck
from torch.testing._internal.jit_utils import JitTestCase
import torch
if __name__ == '__main__':
raise RuntimeError("This test file is not meant to be run directly, use:\n\n"
"\tpython test/test_jit.py TESTNAME\n\n"
... | 1,398 | 34.871795 | 102 | py |
pytorch | pytorch-main/test/jit/test_dce.py | # Owner(s): ["oncall: jit"]
import torch
from torch.testing import FileCheck
from torch.testing._internal.jit_utils import JitTestCase, make_global
class TestDCE(JitTestCase):
def test_setattr_no_aliasdb(self):
class Net(torch.nn.Module):
def __init__(self):
super().__init__()... | 1,239 | 25.382979 | 70 | py |
pytorch | pytorch-main/test/jit/test_ivalue.py | # Owner(s): ["oncall: jit"]
import os
import sys
import torch
# Make the helper files in test/ importable
pytorch_test_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
sys.path.append(pytorch_test_dir)
from torch.testing._internal.jit_utils import JitTestCase
if __name__ == "__main__":
raise R... | 713 | 24.5 | 79 | py |
pytorch | pytorch-main/test/jit/test_cuda.py | # Owner(s): ["oncall: jit"]
import os
import sys
import gc
import unittest
import torch
from typing import NamedTuple
from torch.testing import FileCheck
from torch.testing._internal.jit_utils import JitTestCase
from torch.testing._internal.common_utils import skipIfRocm, skipCUDANonDefaultStreamIf, NoTest
# Make th... | 27,089 | 42.553055 | 109 | py |
pytorch | pytorch-main/test/jit/test_with.py | # Owner(s): ["oncall: jit"]
import os
import sys
from typing import Any, List
import torch
from torch.testing._internal.common_utils import skipIfTorchDynamo
from torch.testing._internal.jit_utils import JitTestCase, make_global
# Make the helper files in test/ importable
pytorch_test_dir = os.path.dirname(os.path... | 19,657 | 30.006309 | 119 | py |
pytorch | pytorch-main/test/jit/test_list_dict.py | # Owner(s): ["oncall: jit"]
import os
import sys
import inspect
import unittest
from typing import Any, Dict, List, NamedTuple, Optional, Tuple
from textwrap import dedent
from collections import OrderedDict
from torch import Tensor
import torch
import torch.nn as nn
import types
from torch.testing import FileCheck
... | 91,253 | 32.475422 | 118 | py |
pytorch | pytorch-main/test/jit/test_freezing.py | # Owner(s): ["oncall: jit"]
import io
import unittest
from itertools import product
from typing import Any
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.jit._recursive import wrap_cpp_module
from torch.testing import FileCheck
from torch.testing._internal.common_quantization import ski... | 114,438 | 36.059262 | 128 | py |
pytorch | pytorch-main/test/jit/test_scriptmod_ann.py | # Owner(s): ["oncall: jit"]
import os
import sys
import warnings
import torch
from typing import List, Dict, Optional
# Make the helper files in test/ importable
pytorch_test_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
sys.path.append(pytorch_test_dir)
from torch.testing._internal.jit_utils im... | 9,351 | 34.831418 | 87 | py |
pytorch | pytorch-main/test/jit/test_backend_nnapi.py | # Owner(s): ["oncall: jit"]
import os
import sys
import unittest
import torch
import torch._C
from pathlib import Path
from test_nnapi import TestNNAPI
# Make the helper files in test/ importable
pytorch_test_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
sys.path.append(pytorch_test_dir)
if __n... | 4,864 | 42.4375 | 132 | py |
pytorch | pytorch-main/test/jit/test_autodiff.py | # Owner(s): ["oncall: jit"]
import torch
from torch.testing._internal.common_utils import skipIfTorchDynamo
from torch.testing._internal.jit_utils import JitTestCase
from typing import List
@skipIfTorchDynamo()
class TestAutodiffJit(JitTestCase):
def test_undefined_tensor_lists(self):
def fn(tensor_list... | 5,115 | 33.567568 | 87 | py |
pytorch | pytorch-main/test/jit/test_tensor_methods.py | # Owner(s): ["oncall: jit"]
import os
import sys
import torch
# Make the helper files in test/ importable
pytorch_test_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
sys.path.append(pytorch_test_dir)
from torch.testing._internal.jit_utils import JitTestCase
from torch.testing import FileCheck
if... | 1,239 | 30 | 80 | py |
pytorch | pytorch-main/test/jit/test_alias_analysis.py | # Owner(s): ["oncall: jit"]
from torch.testing._internal.jit_utils import JitTestCase
from torch._C import parse_ir
import torch
if __name__ == '__main__':
raise RuntimeError("This test file is not meant to be run directly, use:\n\n"
"\tpython test/test_jit.py TESTNAME\n\n"
... | 3,490 | 36.138298 | 103 | py |
pytorch | pytorch-main/test/jit/test_graph_rewrite_passes.py | # Owner(s): ["oncall: jit"]
from torch.testing._internal.jit_utils import JitTestCase
import torch
import torch._C
from torch.testing import FileCheck
class TestGraphRewritePasses(JitTestCase):
def test_fuse_linear(self):
class FunctionalLinear(torch.nn.Module):
def __init__(self, weight, bia... | 2,227 | 34.935484 | 81 | py |
pytorch | pytorch-main/test/jit/test_dtype_analysis.py | # Owner(s): ["oncall: jit"]
from itertools import product
from typing import Tuple
from unittest.case import expectedFailure
import torch
from torch import complex32, float32, float64, int32, int64
from torch.jit._passes import _property_propagation
from torch.testing._internal.common_methods_invocations import (
... | 13,270 | 33.559896 | 97 | py |
pytorch | pytorch-main/test/jit/test_batch_mm.py | # Owner(s): ["oncall: jit"]
import torch
from torch.testing import FileCheck
from torch.testing._internal.jit_utils import JitTestCase
if __name__ == "__main__":
raise RuntimeError(
"This test file is not meant to be run directly, use:\n\n"
"\tpython test/test_jit.py TESTNAME\n\n"
"instead... | 10,140 | 33.848797 | 86 | py |
pytorch | pytorch-main/test/jit/test_symbolic_shape_analysis.py | # Owner(s): ["oncall: jit"]
import operator
import unittest
from textwrap import dedent
import torch
from torch import nn
from torch.testing import FileCheck
from torch.testing._internal.common_methods_invocations import sample_inputs_cat_concat
from torch.testing._internal.common_utils import make_tensor
from torch.... | 27,271 | 42.705128 | 128 | py |
pytorch | pytorch-main/test/jit/test_isinstance.py | # Owner(s): ["oncall: jit"]
import os
import sys
import torch
import warnings
from typing import List, Any, Dict, Tuple, Optional
# Make the helper files in test/ importable
pytorch_test_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
sys.path.append(pytorch_test_dir)
from torch.testing._internal.... | 11,135 | 33.37037 | 87 | py |
pytorch | pytorch-main/test/jit/test_tracer.py | # Owner(s): ["oncall: jit"]
import unittest
import io
import os
import sys
import copy
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable, Function
from torch.testing import FileCheck
# Make the helper files in test/ importable
pytorch_test_dir = os.path.dirname(os... | 90,096 | 33.599462 | 123 | py |
pytorch | pytorch-main/test/jit/xnnpack/test_xnnpack_delegate.py | # Owner(s): ["oncall: jit"]
import unittest
import torch
import torch._C
torch.ops.load_library("//caffe2:xnnpack_backend")
class TestXNNPackBackend(unittest.TestCase):
def test_xnnpack_constant_data(self):
class Module(torch.nn.Module):
def __init__(self):
super().__init__()... | 5,568 | 29.767956 | 99 | py |
pytorch | pytorch-main/test/jit/_imported_class_test/foo.py | import torch
from . import bar
# This file contains definitions of script classes.
# They are used by test_jit.py to test ScriptClass imports
@torch.jit.script # noqa: B903
class FooSameName:
def __init__(self, x):
self.x = x
self.nested = bar.FooSameName(x)
| 282 | 22.583333 | 58 | py |
pytorch | pytorch-main/test/jit/_imported_class_test/bar.py | import torch
# This file contains definitions of script classes.
# They are used by test_jit.py to test ScriptClass imports
@torch.jit.script # noqa: B903
class FooSameName: # noqa: B903
def __init__(self, y):
self.y = y
| 237 | 22.8 | 58 | py |
pytorch | pytorch-main/test/jit/_imported_class_test/very/very/nested.py | import torch
# This file contains definitions of script classes.
# They are used by test_jit.py to test ScriptClass imports
@torch.jit.script # noqa: B903
class FooUniqueName: # noqa: B903
def __init__(self, y):
self.y = y
| 239 | 23 | 58 | py |
pytorch | pytorch-main/test/jit/fixtures_srcs/test_upgrader_models_generation.py | # Owner(s): ["oncall: mobile"]
import torch
from test.jit.fixtures_srcs.generate_models import ALL_MODULES
from torch.testing._internal.common_utils import TestCase, run_tests
class TestUpgraderModelGeneration(TestCase):
def test_all_modules(self):
for a_module, expect_operator in ALL_MODULES.items():
... | 776 | 36 | 92 | py |
pytorch | pytorch-main/test/jit/fixtures_srcs/generate_models.py | import io
import logging
import sys
import zipfile
from pathlib import Path
from typing import Set
import torch
# Use asterisk symbol so developer doesn't need to import here when they add tests for upgraders.
from test.jit.fixtures_srcs.fixtures_src import * # noqa: F403
from torch.jit.mobile import _load_for_lite_i... | 8,892 | 38.878924 | 126 | py |
pytorch | pytorch-main/test/jit/fixtures_srcs/fixtures_src.py | import torch
from typing import Union
class TestVersionedDivTensorExampleV7(torch.nn.Module):
def forward(self, a, b):
result_0 = a / b
result_1 = torch.div(a, b)
result_2 = a.div(b)
return result_0, result_1, result_2
class TestVersionedLinspaceV7(torch.nn.Module):
def forward... | 1,860 | 31.086207 | 103 | py |
pytorch | pytorch-main/test/onnx/test_export_modes.py | # Owner(s): ["module: onnx"]
import io
import os
import shutil
import sys
import tempfile
import torch
import torch.nn as nn
from torch.autograd import Variable
from torch.onnx import OperatorExportTypes
# Make the helper files in test/ importable
pytorch_test_dir = os.path.dirname(os.path.dirname(os.path.realpath(_... | 4,490 | 28.94 | 79 | py |
pytorch | pytorch-main/test/onnx/test_custom_ops.py | # Owner(s): ["module: onnx"]
import onnx_test_common
import pytorch_test_common
import torch
import torch.utils.cpp_extension
from torch.onnx import symbolic_helper
from torch.testing._internal import common_utils
class TestCustomAutogradFunction(pytorch_test_common.ExportTestCase):
opset_version = 9
keep_in... | 3,970 | 31.818182 | 84 | py |
pytorch | pytorch-main/test/onnx/test_fx_op_consistency.py | # Owner(s): ["module: onnx"]
"""Test consistency between the output values of torch.onnx FX exported operators
and torch operators given the same inputs.
Usage:
pytest test/onnx/test_op_consistency.py
To run tests on a specific operator (e.g. torch.ceil):
pytest test/onnx/test_op_consistency.py -k ceil... | 21,222 | 32.527646 | 115 | py |
pytorch | pytorch-main/test/onnx/test_fx_to_onnx.py | # Owner(s): ["module: onnx"]
from __future__ import annotations
import tempfile
import onnx
import pytest
import pytorch_test_common
import torch
from torch import nn
from torch._subclasses import fake_tensor
from torch.nn import functional as F
from torch.onnx import dynamo_export, ExportOptions
from torch.onnx._int... | 14,238 | 37.174263 | 92 | py |
pytorch | pytorch-main/test/onnx/pytorch_test_common.py | # Owner(s): ["module: onnx"]
from __future__ import annotations
import functools
import os
import random
import sys
import unittest
from typing import Optional
import numpy as np
import packaging.version
import torch
from torch.autograd import function
from torch.onnx._internal import diagnostics
from torch.testing.... | 9,485 | 27.65861 | 97 | py |
pytorch | pytorch-main/test/onnx/test_models_quantized_onnxruntime.py | # Owner(s): ["module: onnx"]
import os
import unittest
import onnx_test_common
import parameterized
import PIL
import torch
import torchvision
from torch import nn
def _get_test_image_tensor():
data_dir = os.path.join(os.path.dirname(__file__), "assets")
img_path = os.path.join(data_dir, "grace_hopper_517x... | 3,322 | 32.908163 | 94 | py |
pytorch | pytorch-main/test/onnx/test_pytorch_jit_onnx.py | # Owner(s): ["module: onnx"]
import onnxruntime
import pytorch_test_common
import torch
from pytorch_test_common import skipIfNoCuda
from torch.onnx import verification
from torch.testing._internal import common_utils
def _jit_graph_to_onnx_model(graph, operator_export_type, opset_version):
r"""
This functio... | 5,934 | 30.737968 | 121 | py |
pytorch | pytorch-main/test/onnx/debug_embed_params.py | import sys
import caffe2.python.onnx.backend as c2
import onnx
import pytorch_test_common
import torch
import torch.jit
from torch.autograd import Variable
torch.set_default_tensor_type("torch.FloatTensor")
try:
import torch
except ImportError:
print("Cannot import torch, hence caffe2-torch test will not run... | 1,535 | 26.927273 | 79 | py |
pytorch | pytorch-main/test/onnx/test_pytorch_onnx_onnxruntime_cuda.py | # Owner(s): ["module: onnx"]
import unittest
import onnx_test_common
import onnxruntime # noqa: F401
import parameterized
import torch
from pytorch_test_common import (
skipIfNoBFloat16Cuda,
skipIfNoCuda,
skipIfUnsupportedMinOpsetVersion,
skipScriptTest,
)
from test_pytorch_onnx_onnxruntime import ... | 4,879 | 30.082803 | 87 | py |
pytorch | pytorch-main/test/onnx/test_fx_type_promotion.py | # Owner(s): ["module: onnx"]
import pytorch_test_common
from torch.onnx._internal.fx.passes import type_promotion
from torch.testing._internal import common_utils
class TestGeneratedTypePromotionRuleSet(common_utils.TestCase):
@pytorch_test_common.skip_in_ci(
"Reduce noise in CI. "
"The test serv... | 857 | 30.777778 | 86 | py |
pytorch | pytorch-main/test/onnx/verify.py | import difflib
import io
import numpy as np
import onnx
import onnx.helper
import torch
import torch.jit
import torch.onnx
def colonize(msg, sep=": "):
if not msg:
return ""
else:
return msg + sep
class Errors:
"""
An error-collecting object which supports error recovery.
It i... | 20,957 | 38.543396 | 101 | py |
pytorch | pytorch-main/test/onnx/test_pytorch_onnx_shape_inference.py | # Owner(s): ["module: onnx"]
import io
import numpy as np
import onnx
import pytorch_test_common
import torch
from pytorch_test_common import skipIfUnsupportedMinOpsetVersion
from torch.onnx import _constants, symbolic_helper
from torch.onnx._internal import jit_utils
from torch.testing._internal import common_utils
... | 20,682 | 41.210204 | 96 | py |
pytorch | pytorch-main/test/onnx/test_onnxscript_runtime.py | # Owner(s): ["module: onnx"]
"""Test the support on onnxscript in PyTorch-ONNX converter with onnxruntime."""
from typing import List
import onnx_test_common
import onnxscript
import torch
from onnxscript.onnx_types import FLOAT
from torch.onnx._internal import jit_utils
from torch.testing._internal import common_uti... | 4,514 | 34.273438 | 96 | py |
pytorch | pytorch-main/test/onnx/test_pytorch_onnx_no_runtime.py | # Owner(s): ["module: onnx"]
"""Tests for onnx export that don't run the exported model."""
from __future__ import annotations
import contextlib
import io
import itertools
import unittest
import unittest.mock
import warnings
from typing import Callable, Dict, Iterable, List, Optional, Tuple, Union
import numpy as n... | 46,948 | 34.976245 | 106 | py |
pytorch | pytorch-main/test/onnx/test_fx_passes.py | # Owner(s): ["module: onnx"]
import torch
import torch._dynamo
import torch.fx
from torch._custom_op import impl as custom_op
from torch.onnx._internal.fx.passes import _utils as pass_utils
from torch.testing._internal import common_utils
class TestFxPasses(common_utils.TestCase):
def test_set_node_name_correctl... | 3,554 | 32.224299 | 88 | py |
pytorch | pytorch-main/test/onnx/pytorch_helper.py | import io
import onnx
import torch.onnx
from caffe2.python.core import BlobReference, Net
from caffe2.python.onnx.backend import Caffe2Backend
_next_idx = 0
# Clone net takes a dict instead of a lambda
# It should probably take a lambda, it is more flexible
# We fake dict here
class _FakeDict:
def __init__(sel... | 3,381 | 35.365591 | 84 | py |
pytorch | pytorch-main/test/onnx/test_fx_to_onnx_with_onnxruntime.py | # Owner(s): ["module: onnx"]
from __future__ import annotations
import itertools
import os
import tempfile
import unittest
from typing import Any, Callable, Dict, List, Mapping, Optional, Tuple, Type
import onnx_test_common
import onnxruntime # type: ignore[import]
import parameterized
import pytorch_test_common
im... | 35,308 | 36.642857 | 115 | py |
pytorch | pytorch-main/test/onnx/test_models.py | # Owner(s): ["module: onnx"]
import unittest
import pytorch_test_common
import torch
from model_defs.dcgan import _netD, _netG, bsz, imgsz, nz, weights_init
from model_defs.emb_seq import EmbeddingNetwork1, EmbeddingNetwork2
from model_defs.mnist import MNIST
from model_defs.op_test import ConcatNet, DummyNet, FakeQ... | 10,947 | 37.146341 | 94 | py |
pytorch | pytorch-main/test/onnx/test_operators.py | # Owner(s): ["module: onnx"]
"""
Usage: python test/onnx/test_operators.py [--no-onnx] [--produce-onnx-test-data]
--no-onnx: no onnx python dependency
--produce-onnx-test-data: generate onnx test data
--accept: accept onnx updates and overwrite models
"""
import glob
import inspect
import... | 46,661 | 34.783742 | 112 | py |
pytorch | pytorch-main/test/onnx/test_op_consistency.py | # Owner(s): ["module: onnx"]
"""Test consistency between the output values of torch.onnx exported operators
and torch operators given the same inputs.
Usage:
pytest test/onnx/test_op_consistency.py
To run tests on a specific operator (e.g. torch.ceil):
pytest test/onnx/test_op_consistency.py -k ceil
... | 12,867 | 38.351682 | 127 | py |
pytorch | pytorch-main/test/onnx/test_models_onnxruntime.py | # Owner(s): ["module: onnx"]
import os
import unittest
from collections import OrderedDict
from typing import List, Mapping, Tuple
import onnx_test_common
import parameterized
import PIL
import pytorch_test_common
import test_models
import torch
import torchvision
from pytorch_test_common import skipIfUnsupportedMin... | 14,313 | 31.311512 | 88 | py |
pytorch | pytorch-main/test/onnx/test_utility_funs.py | # Owner(s): ["module: onnx"]
import copy
import functools
import io
import re
import warnings
from typing import Callable
import onnx
import parameterized
import pytorch_test_common
import torch
import torch.onnx
import torch.utils.cpp_extension
import torchvision
from autograd_helper import CustomFunction as Custom... | 71,755 | 35.911523 | 124 | py |
pytorch | pytorch-main/test/onnx/test_onnxscript_no_runtime.py | # Owner(s): ["module: onnx"]
"""Test the support on onnxscript in PyTorch-ONNX converter."""
import io
from typing import List
import onnx
import onnxscript
import torch
from onnxscript.onnx_types import FLOAT
from torch.onnx._internal import jit_utils
from torch.testing._internal import common_utils
class TestONNX... | 6,170 | 36.858896 | 90 | py |
pytorch | pytorch-main/test/onnx/autograd_helper.py | # Owner(s): ["module: onnx"]
import torch
# Autograd funtion that is a replica of the autograd funtion in
# test_utility_funs.py (test_autograd_module_name)
class CustomFunction(torch.autograd.Function):
@staticmethod
def forward(ctx, input):
ctx.save_for_backward(input)
return input.clamp(mi... | 518 | 24.95 | 63 | py |
pytorch | pytorch-main/test/onnx/test_autograd_funs.py | # Owner(s): ["module: onnx"]
import pytorch_test_common
import torch
from onnx_test_common import run_model_test
from torch.onnx import OperatorExportTypes
from torch.onnx._globals import GLOBALS
from torch.onnx.utils import _model_to_graph
from torch.testing._internal import common_utils
class TestAutogradFuns(pyt... | 6,730 | 30.600939 | 73 | py |
pytorch | pytorch-main/test/onnx/onnx_test_common.py | # Owner(s): ["module: onnx"]
from __future__ import annotations
import contextlib
import copy
import dataclasses
import io
import os
import unittest
import warnings
from typing import (
Any,
Callable,
Collection,
Iterable,
List,
Mapping,
Optional,
Sequence,
Tuple,
Type,
Un... | 22,216 | 31.914074 | 124 | py |
pytorch | pytorch-main/test/onnx/test_symbolic_helper.py | # Owner(s): ["module: onnx"]
"""Unit tests on `torch.onnx.symbolic_helper`."""
import torch
from torch.onnx import symbolic_helper
from torch.onnx._globals import GLOBALS
from torch.testing._internal import common_utils
class TestHelperFunctions(common_utils.TestCase):
def setUp(self):
super().setUp()
... | 2,292 | 30.847222 | 85 | py |
pytorch | pytorch-main/test/onnx/test_pytorch_onnx_onnxruntime.py | # Owner(s): ["module: onnx"]
from __future__ import annotations
import io
import itertools
import os
import unittest
from collections import OrderedDict
from typing import Dict, List, Optional, Tuple, Type, Union
import numpy as np
import onnx
import onnx_test_common
import parameterized
import torch
import torchvis... | 474,004 | 34.265605 | 119 | py |
pytorch | pytorch-main/test/onnx/test_verification.py | # Owner(s): ["module: onnx"]
import contextlib
import io
import tempfile
import unittest
import numpy as np
import onnx
import parameterized
import pytorch_test_common
import torch
from packaging import version
from torch.onnx import _constants, _experimental, verification
from torch.testing._internal import common_... | 9,900 | 32.449324 | 103 | py |
pytorch | pytorch-main/test/onnx/test_onnx_opset.py | # Owner(s): ["module: onnx"]
import io
import itertools
import onnx
import pytorch_test_common
import torch
import torch.onnx
from torch.nn import Module
from torch.onnx import producer_name, producer_version
from torch.onnx._globals import GLOBALS
from torch.testing._internal import common_utils
def check_onnx_op... | 17,504 | 31.476809 | 87 | py |
pytorch | pytorch-main/test/onnx/model_defs/word_language_model.py | # The model is from here:
# https://github.com/pytorch/examples/blob/master/word_language_model/model.py
from typing import Optional, Tuple
import torch
import torch.nn as nn
from torch import Tensor
class RNNModel(nn.Module):
"""Container module with an encoder, a recurrent module, and a decoder."""
def... | 4,642 | 33.649254 | 110 | py |
pytorch | pytorch-main/test/onnx/model_defs/rnn_model_with_packed_sequence.py | from torch import nn
from torch.nn.utils import rnn as rnn_utils
class RnnModelWithPackedSequence(nn.Module):
def __init__(self, model, batch_first):
super().__init__()
self.model = model
self.batch_first = batch_first
def forward(self, input, *args):
args, seq_lengths = args[... | 1,626 | 34.369565 | 84 | py |
pytorch | pytorch-main/test/onnx/model_defs/lstm_flattening_result.py | from torch import nn
from torch.nn.utils.rnn import PackedSequence
class LstmFlatteningResult(nn.LSTM):
def forward(self, input, *fargs, **fkwargs):
output, (hidden, cell) = nn.LSTM.forward(self, input, *fargs, **fkwargs)
return output, hidden, cell
class LstmFlatteningResultWithSeqLength(nn.Mod... | 1,503 | 31 | 88 | py |
pytorch | pytorch-main/test/onnx/model_defs/emb_seq.py | import torch.nn as nn
class EmbeddingNetwork1(nn.Module):
def __init__(self, dim=5):
super().__init__()
self.emb = nn.Embedding(10, dim)
self.lin1 = nn.Linear(dim, 1)
self.seq = nn.Sequential(
self.emb,
self.lin1,
)
def forward(self, input):
... | 658 | 24.346154 | 81 | py |
pytorch | pytorch-main/test/onnx/model_defs/squeezenet.py | import torch
import torch.nn as nn
import torch.nn.init as init
class Fire(nn.Module):
def __init__(self, inplanes, squeeze_planes, expand1x1_planes, expand3x3_planes):
super().__init__()
self.inplanes = inplanes
self.squeeze = nn.Conv2d(inplanes, squeeze_planes, kernel_size=1)
sel... | 3,539 | 38.333333 | 85 | py |
pytorch | pytorch-main/test/onnx/model_defs/dcgan.py | import torch
import torch.nn as nn
# configurable
bsz = 64
imgsz = 64
nz = 100
ngf = 64
ndf = 64
nc = 3
# custom weights initialization called on netG and netD
def weights_init(m):
classname = m.__class__.__name__
if classname.find("Conv") != -1:
m.weight.data.normal_(0.0, 0.02)
elif classname.fi... | 2,951 | 31.8 | 82 | py |
pytorch | pytorch-main/test/onnx/model_defs/op_test.py | # Owner(s): ["module: onnx"]
import torch
import torch.nn as nn
class DummyNet(nn.Module):
def __init__(self, num_classes=1000):
super().__init__()
self.features = nn.Sequential(
nn.LeakyReLU(0.02),
nn.BatchNorm2d(3),
nn.AvgPool2d(kernel_size=3, stride=2, paddi... | 1,171 | 21.538462 | 78 | py |
pytorch | pytorch-main/test/onnx/model_defs/super_resolution.py | import torch.nn as nn
import torch.nn.init as init
class SuperResolutionNet(nn.Module):
def __init__(self, upscale_factor):
super().__init__()
self.relu = nn.ReLU()
self.conv1 = nn.Conv2d(1, 64, (5, 5), (1, 1), (2, 2))
self.conv2 = nn.Conv2d(64, 64, (3, 3), (1, 1), (1, 1))
... | 1,051 | 34.066667 | 77 | py |
pytorch | pytorch-main/test/onnx/model_defs/srresnet.py | import math
from torch import nn
from torch.nn import init
def _initialize_orthogonal(conv):
prelu_gain = math.sqrt(2)
init.orthogonal(conv.weight, gain=prelu_gain)
if conv.bias is not None:
conv.bias.data.zero_()
class ResidualBlock(nn.Module):
def __init__(self, n_filters):
super(... | 3,228 | 32.989474 | 86 | py |
pytorch | pytorch-main/test/onnx/model_defs/mnist.py | import torch.nn as nn
import torch.nn.functional as F
class MNIST(nn.Module):
def __init__(self):
super().__init__()
self.conv1 = nn.Conv2d(1, 10, kernel_size=5)
self.conv2 = nn.Conv2d(10, 20, kernel_size=5)
self.conv2_drop = nn.Dropout2d()
self.fc1 = nn.Linear(320, 50)
... | 672 | 29.590909 | 67 | py |
pytorch | pytorch-main/test/onnx/dynamo/test_exporter_api.py | # Owner(s): ["module: onnx"]
import io
import logging
import os
import onnx
import torch
from beartype import roar
from torch.onnx import dynamo_export, ExportOptions, ExportOutput
from torch.onnx._internal import exporter, io_adapter
from torch.onnx._internal.diagnostics import infra
from torch.onnx._internal.exporte... | 6,822 | 37.988571 | 88 | py |
pytorch | pytorch-main/test/onnx/dynamo/test_registry_dispatcher.py | # Owner(s): ["module: onnx"]
"""Unit tests for the internal registration wrapper module."""
from __future__ import annotations
import logging
import operator
from typing import TypeVar, Union
import onnxscript # type: ignore[import]
import torch
import torch.fx
from onnxscript import BFLOAT16, DOUBLE, FLOAT, FLOAT1... | 17,619 | 36.172996 | 113 | py |
pytorch | pytorch-main/test/onnx/internal/test_beartype.py | # Owner(s): ["module: onnx"]
"""Unit tests for the internal beartype wrapper module."""
import unittest
from torch.onnx._internal import _beartype
from torch.testing._internal import common_utils
def beartype_installed():
try:
import beartype # noqa: F401
except ImportError:
return False
... | 2,783 | 31.752941 | 83 | py |
pytorch | pytorch-main/test/onnx/internal/test_diagnostics.py | # Owner(s): ["module: onnx"]
from __future__ import annotations
import contextlib
import dataclasses
import io
import logging
import typing
import unittest
from typing import AbstractSet, Protocol, Tuple
import torch
from torch.onnx import errors
from torch.onnx._internal import diagnostics
from torch.onnx._internal.... | 10,932 | 32.64 | 106 | py |
pytorch | pytorch-main/test/onnx/internal/test_registraion.py | # Owner(s): ["module: onnx"]
"""Unit tests for the internal registration wrapper module."""
from typing import Sequence
from torch.onnx import errors
from torch.onnx._internal import registration
from torch.testing._internal import common_utils
@common_utils.instantiate_parametrized_tests
class TestGlobalHelpers(co... | 9,767 | 37.305882 | 84 | py |
pytorch | pytorch-main/test/functorch/test_memory_efficient_fusion.py | # Owner(s): ["module: functorch"]
import torch
import torch.nn as nn
import torch.fx as fx
from functorch import make_fx
from torch.nn import functional as F
from functorch.compile import memory_efficient_fusion
from torch._functorch.compile_utils import fx_graph_cse
from torch.testing._internal.common_utils import Te... | 11,537 | 30.016129 | 124 | py |
pytorch | pytorch-main/test/functorch/test_logging.py | # Owner(s): ["module: dynamo"]
import torch
from torch.testing._internal.logging_utils import LoggingTestCase, make_logging_test
from torch._functorch.aot_autograd import aot_function
from torch._functorch.compilers import nop
import logging
class TestAOTLogging(LoggingTestCase):
@make_logging_test(aot=logging.DE... | 608 | 28 | 84 | py |
pytorch | pytorch-main/test/functorch/attn_positional.py | # Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import torch
from torch import nn
import math
class BertSelfAttention(nn.Module):
def __init__(self, hidden_s... | 4,406 | 45.882979 | 115 | py |
pytorch | pytorch-main/test/functorch/test_parsing.py | # Owner(s): ["module: functorch"]
"""Adapted from https://github.com/arogozhnikov/einops/blob/230ac1526c1f42c9e1f7373912c7f8047496df11/tests/test_parsing.py.
MIT License
Copyright (c) 2018 Alex Rogozhnikov
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated d... | 10,492 | 41.828571 | 123 | py |
pytorch | pytorch-main/test/functorch/test_vmap.py | # Owner(s): ["module: functorch"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
from typing import OrderedDict
from unittest.case import skipIf
from torch.tes... | 211,235 | 39.794902 | 119 | py |
pytorch | pytorch-main/test/functorch/test_aotdispatch.py | # Owner(s): ["oncall: pt2"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
from typing import Union, Callable, List, Any, Optional, Dict
from unittest.mock imp... | 135,053 | 43.928144 | 279 | py |
pytorch | pytorch-main/test/functorch/xfail_suggester.py | import re
import torch
"""
Instructions:
1. pytest -n 8 test/test_vmap.py test/test_ops.py test/test_aotdispatch.py > result.txt
2. python test/xfail_suggester.py
"""
with open('result.txt') as f:
lines = f.readlines()
failed = [line for line in lines if line.startswith('FAILED')]
p = re.compile('FAILED test/te... | 3,756 | 24.732877 | 87 | py |
pytorch | pytorch-main/test/functorch/test_minifier.py | # Owner(s): ["module: functorch"]
import torch
from functorch.compile import minifier
from torch._functorch.compile_utils import get_placeholders, get_outputs
from functorch import make_fx
from torch.testing._internal.common_utils import TestCase, run_tests
class TestMinifier(TestCase):
def test_has_mul_minifier... | 3,557 | 29.410256 | 86 | py |
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