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
value |
|---|---|---|---|---|---|---|
pytorch | pytorch-main/torch/fx/passes/shape_prop.py | import torch
import torch.fx
import traceback
from torch._dispatch.python import enable_python_dispatcher
from torch.fx.node import Node, map_aggregate
from typing import Any, Tuple, NamedTuple, Optional, Dict
from torch.fx._compatibility import compatibility
from torch._guards import detect_fake_mode
__all__ = ['Ten... | 7,103 | 35.618557 | 120 | py |
pytorch | pytorch-main/torch/fx/passes/annotate_getitem_nodes.py | import operator
import torch
def annotate_getitem_nodes(graph: torch.fx.Graph) -> None:
"""
Annotate the type of getitem nodes, inferred from the type of sequence node.
If sequence node is not annotated with a type, do nothing.
Currently support getitem nodes from Tuple, List, and NamedTuple sequence... | 1,869 | 42.488372 | 99 | py |
pytorch | pytorch-main/torch/fx/passes/operator_support.py | import abc
import typing as t
import torch
import torch.fx
from torch.fx._compatibility import compatibility
from .shape_prop import TensorMetadata
from .tools_common import get_node_target, CALLABLE_NODE_OPS
__all__ = ['OperatorSupportBase', 'OperatorSupport', 'create_op_support', 'chain', 'OpSupports', 'any_chain'... | 7,829 | 34.429864 | 109 | py |
pytorch | pytorch-main/torch/fx/passes/param_fetch.py | from torch.fx.graph_module import GraphModule
from typing import Any, Callable, Dict, List, Tuple, Type
import torch
import torch.nn as nn
from torch.fx._compatibility import compatibility
__all__ = ['default_matching', 'extract_attrs_for_lowering', 'lift_lowering_attrs_to_nodes']
# Matching method matches the attri... | 3,527 | 51.656716 | 124 | py |
pytorch | pytorch-main/torch/fx/passes/graph_manipulation.py | from typing import Any, Dict, List, NamedTuple, Optional
import torch
from torch.fx._compatibility import compatibility
from torch.fx.graph import Graph
from torch.fx.graph_module import GraphModule
from torch.fx.node import (
map_arg,
Node,
Target,
)
from torch.fx.passes.shape_prop import ShapeProp
__all... | 3,981 | 34.873874 | 97 | py |
pytorch | pytorch-main/torch/fx/passes/tools_common.py | from typing import List, Tuple, Union, Dict, Any, Set, Mapping
import collections
from dataclasses import dataclass
import torch
import torch.fx
from torch.fx.node import _get_qualified_name
from torch.fx._compatibility import compatibility
__all__ = ['get_acc_ops_name', 'get_node_target', 'is_node_output_tensor', 'F... | 9,570 | 36.533333 | 117 | py |
pytorch | pytorch-main/torch/fx/passes/split_utils.py | from dataclasses import dataclass, field
from typing import List, Optional, Dict
import torch.fx
from torch.fx.graph import map_arg
from .tools_common import NodeList
from torch.fx._compatibility import compatibility
from torch.fx.passes.utils import lift_subgraph_as_module, HolderModule
__all__ = ['getattr_recursive... | 10,279 | 35.978417 | 110 | py |
pytorch | pytorch-main/torch/fx/passes/fake_tensor_prop.py | from typing import Optional
import torch.fx
from torch.fx import Node
from torch.fx._compatibility import compatibility
from torch._subclasses.fake_tensor import FakeTensorMode, FakeTensor
from torch.fx.experimental.proxy_tensor import py_sym_types, snapshot_fake
from torch.fx.node import map_aggregate
__all__ = ['Fa... | 2,299 | 36.096774 | 114 | py |
pytorch | pytorch-main/torch/fx/passes/net_min_base.py | import logging
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Tuple
import torch
import torch.fx
from torch.fx._compatibility import compatibility
from torch.fx.node import map_arg
from .shape_prop import ShapeProp
from .split_utils import split_by_tags
from .tools_common im... | 21,724 | 34.096931 | 93 | py |
pytorch | pytorch-main/torch/fx/passes/graph_drawer.py |
import hashlib
import torch
import torch.fx
from typing import Dict, Any, TYPE_CHECKING
from torch.fx.node import _get_qualified_name, _format_arg
from torch.fx.passes.shape_prop import TensorMetadata
from torch.fx._compatibility import compatibility
from itertools import chain
__all__ = ['FxGraphDrawer']
try:
im... | 13,744 | 38.497126 | 122 | py |
pytorch | pytorch-main/torch/fx/passes/backends/cudagraphs.py | import torch
from torch.fx.passes.infra.partitioner import CapabilityBasedPartitioner
from torch.fx.passes.operator_support import OperatorSupport
from torch.fx.passes.tools_common import CALLABLE_NODE_OPS
from torch.fx.passes.fake_tensor_prop import FakeTensorProp
from torch.utils._pytree import tree_map
import opera... | 2,023 | 34.508772 | 98 | py |
pytorch | pytorch-main/torch/fx/passes/infra/partitioner.py | from typing import Dict, List, Set, Iterable, Sequence, Optional, Deque
from torch.fx.passes.utils.fuser_utils import fuse_by_partitions
from torch.fx.graph_module import GraphModule
from torch.fx.node import Node, _get_qualified_name
from torch.fx.passes.operator_support import OperatorSupportBase
import logging
im... | 12,689 | 44.483871 | 105 | py |
pytorch | pytorch-main/torch/fx/passes/infra/pass_base.py | import abc
from collections import namedtuple
from typing import Optional
from torch.fx.graph_module import GraphModule
from torch.fx._compatibility import compatibility
__all__ = ['PassResult', 'PassBase']
@compatibility(is_backward_compatible=False)
class PassResult(namedtuple("PassResult", ["graph_module", "modi... | 2,490 | 31.776316 | 82 | py |
pytorch | pytorch-main/torch/fx/passes/infra/pass_manager.py | import inspect
import logging
from queue import Queue
from functools import wraps
from typing import Callable, Dict, List
import torch.nn as nn
from torch.fx.graph_module import GraphModule
from torch.fx._compatibility import compatibility
from torch.fx.passes.infra.pass_base import PassResult
logger = logging.getLog... | 10,311 | 32.921053 | 126 | py |
pytorch | pytorch-main/torch/fx/passes/dialect/common/cse_pass.py | from typing import Dict, Tuple, Any
import torch
from torch.fx.passes.infra.pass_base import PassBase, PassResult
from torch.utils._pytree import tree_flatten
from torch.fx import GraphModule, Graph
from torch.fx import Node
aten = torch.ops.aten
# stateful ops are banned from CSE
rand_ops = {aten.dropout, aten._f... | 4,911 | 42.469027 | 264 | py |
pytorch | pytorch-main/torch/fx/passes/utils/source_matcher_utils.py | from dataclasses import dataclass, field
from torch.fx.graph import Graph
from torch.fx.node import Node
from torch.fx._compatibility import compatibility
from typing import Dict, List, Any, Type
import logging
import os
__all__ = ['get_source_partitions', 'check_subgraphs_connected', 'SourcePartition']
# Set`PYTORC... | 4,136 | 31.069767 | 94 | py |
pytorch | pytorch-main/torch/fx/passes/utils/fuser_utils.py | import copy
from queue import SimpleQueue
from typing import List, Dict, Tuple
import torch.fx
from torch.fx.graph_module import GraphModule
from torch.fx.graph import Graph
from torch.fx.node import Node
from torch.fx.passes.tools_common import NodeList, NodeSet, legalize_graph
from torch.fx.passes.utils import lift_... | 8,620 | 35.84188 | 118 | py |
pytorch | pytorch-main/torch/fx/passes/utils/common.py | from torch.nn import Module
from torch.fx.graph_module import GraphModule
from torch.fx.graph import Graph
from torch.fx.passes.utils.matcher_utils import SubgraphMatcher
from torch.fx._compatibility import compatibility
__all__ = ['HolderModule', 'lift_subgraph_as_module', 'compare_graphs']
@compatibility(is_backw... | 2,817 | 32.547619 | 115 | py |
pytorch | pytorch-main/torch/fx/passes/utils/matcher_utils.py | from dataclasses import dataclass, field
from collections import defaultdict
import copy
import torch
from torch.fx.graph import Graph
from torch.fx.node import Node
from torch.fx._compatibility import compatibility
from typing import Dict, List, Set, Any, Union, Tuple
import logging
import os
__all__ = ['SubgraphMatc... | 16,427 | 41.89295 | 118 | py |
pytorch | pytorch-main/torch/fft/__init__.py | import sys
import torch
from torch._C import _add_docstr, _fft # type: ignore[attr-defined]
from torch._torch_docs import factory_common_args, common_args
__all__ = ['fft', 'ifft', 'fft2', 'ifft2', 'fftn', 'ifftn',
'rfft', 'irfft', 'rfft2', 'irfft2', 'rfftn', 'irfftn',
'hfft', 'ihfft', 'fftfreq... | 55,060 | 39.456282 | 109 | py |
pytorch | pytorch-main/.circleci/generate_config_yml.py | #!/usr/bin/env python3
"""
This script is the source of truth for config.yml.
Please see README.md in this directory for details.
"""
import os
import shutil
import sys
from collections import namedtuple
import cimodel.data.simple.docker_definitions
import cimodel.data.simple.mobile_definitions
import cimodel.data.s... | 6,116 | 30.209184 | 109 | py |
pytorch | pytorch-main/.circleci/cimodel/data/binary_build_definitions.py | from collections import OrderedDict
import cimodel.data.simple.util.branch_filters as branch_filters
import cimodel.data.binary_build_data as binary_build_data
import cimodel.lib.conf_tree as conf_tree
import cimodel.lib.miniutils as miniutils
class Conf(object):
def __init__(self, os, gpu_version, pydistro, parm... | 8,602 | 34.258197 | 127 | py |
pytorch | pytorch-main/.circleci/cimodel/data/binary_build_data.py | """
This module models the tree of configuration variants
for "smoketest" builds.
Each subclass of ConfigNode represents a layer of the configuration hierarchy.
These tree nodes encapsulate the logic for whether a branch of the hierarchy
should be "pruned".
"""
from collections import OrderedDict
from cimodel.lib.co... | 5,595 | 31.534884 | 117 | py |
pytorch | pytorch-main/.circleci/cimodel/data/pytorch_build_data.py | from cimodel.lib.conf_tree import ConfigNode
CONFIG_TREE_DATA = [
]
def get_major_pyver(dotted_version):
parts = dotted_version.split(".")
return "py" + parts[0]
class TreeConfigNode(ConfigNode):
def __init__(self, parent, node_name, subtree):
super().__init__(parent, self.modify_label(node_na... | 7,734 | 25.672414 | 98 | py |
pytorch | pytorch-main/.circleci/cimodel/data/pytorch_build_definitions.py | from collections import OrderedDict
from dataclasses import dataclass, field
from typing import List, Optional
import cimodel.data.dimensions as dimensions
import cimodel.lib.conf_tree as conf_tree
import cimodel.lib.miniutils as miniutils
from cimodel.data.pytorch_build_data import CONFIG_TREE_DATA, TopLevelNode
from... | 14,050 | 35.496104 | 116 | py |
pytorch | pytorch-main/.circleci/cimodel/data/simple/macos_definitions.py | class MacOsJob:
def __init__(self, os_version, is_build=False, is_test=False, extra_props=tuple()):
# extra_props is tuple type, because mutable data structures for argument defaults
# is not recommended.
self.os_version = os_version
self.is_build = is_build
self.is_test = is... | 1,703 | 29.981818 | 90 | py |
pytorch | pytorch-main/.circleci/cimodel/data/simple/docker_definitions.py | from collections import OrderedDict
from cimodel.lib.miniutils import quote
from cimodel.data.simple.util.branch_filters import gen_filter_dict, RC_PATTERN
# NOTE: All hardcoded docker image builds have been migrated to GHA
IMAGE_NAMES = [
]
# This entry should be an element from the list above
# This should contai... | 1,481 | 36.05 | 79 | py |
pytorch | pytorch-main/.circleci/cimodel/data/simple/anaconda_prune_defintions.py | from collections import OrderedDict
from cimodel.data.simple.util.branch_filters import gen_filter_dict
from cimodel.lib.miniutils import quote
CHANNELS_TO_PRUNE = ["pytorch-nightly", "pytorch-test"]
PACKAGES_TO_PRUNE = "pytorch torchvision torchaudio torchtext ignite torchcsprng"
def gen_workflow_job(channel: str... | 851 | 28.37931 | 81 | py |
pytorch | pytorch-main/.circleci/cimodel/data/simple/mobile_definitions.py | """
PyTorch Mobile PR builds (use linux host toolchain + mobile build options)
"""
import cimodel.lib.miniutils as miniutils
import cimodel.data.simple.util.branch_filters
class MobileJob:
def __init__(
self,
docker_image,
docker_requires,
variant_parts,
... | 1,391 | 24.777778 | 93 | py |
pytorch | pytorch-main/.circleci/cimodel/data/simple/nightly_ios.py | import cimodel.data.simple.ios_definitions as ios_definitions
import cimodel.lib.miniutils as miniutils
class IOSNightlyJob:
def __init__(self,
variant,
is_full_jit=False,
is_upload=False):
self.variant = variant
self.is_full_jit = is_full_jit
... | 2,587 | 29.093023 | 92 | py |
pytorch | pytorch-main/.circleci/cimodel/data/simple/ios_definitions.py | from cimodel.data.simple.util.versions import MultiPartVersion
from cimodel.data.simple.util.branch_filters import gen_filter_dict_exclude
import cimodel.lib.miniutils as miniutils
XCODE_VERSION = MultiPartVersion([12, 5, 1])
class ArchVariant:
def __init__(self, name, custom_build_name=""):
self.name = ... | 3,069 | 35.987952 | 101 | py |
pytorch | pytorch-main/.circleci/cimodel/data/simple/util/docker_constants.py | AWS_DOCKER_HOST = "308535385114.dkr.ecr.us-east-1.amazonaws.com"
def gen_docker_image(container_type):
return (
"/".join([AWS_DOCKER_HOST, "pytorch", container_type]),
f"docker-{container_type}",
)
def gen_docker_image_requires(image_name):
return [f"docker-{image_name}"]
DOCKER_IMAGE_BA... | 946 | 26.852941 | 80 | py |
pytorch | pytorch-main/test/test_kernel_launch_checks.py | # Owner(s): ["module: unknown"]
from torch.testing._internal.common_utils import TestCase, run_tests
from torch.testing._internal.check_kernel_launches import (
check_cuda_kernel_launches, check_code_for_cuda_kernel_launches
)
class AlwaysCheckCudaLaunchTest(TestCase):
def test_check_code(self):
"""V... | 3,207 | 38.121951 | 86 | py |
pytorch | pytorch-main/test/test_unary_ufuncs.py | # Owner(s): ["module: tests"]
import torch
import numpy as np
import math
from numbers import Number
import random
import unittest
from torch import inf, nan
from torch.testing._internal.common_utils import (
TestCase,
run_tests,
torch_to_numpy_dtype_dict,
numpy_to_torch_dtype_dict,
suppress_warn... | 65,544 | 40.775016 | 126 | py |
pytorch | pytorch-main/test/test_bundled_inputs.py | #!/usr/bin/env python3
# Owner(s): ["oncall: mobile"]
import io
import textwrap
from typing import List, Optional, Dict
import torch
import torch.utils.bundled_inputs
from torch.testing._internal.common_utils import TestCase, run_tests
def model_size(sm):
buffer = io.BytesIO()
torch.jit.save(sm, buffer)
... | 16,454 | 36.060811 | 113 | py |
pytorch | pytorch-main/test/test_nestedtensor.py | # Owner(s): ["module: nestedtensor"]
import unittest
from functools import partial
import numpy as np
import torch
import torch.nn
from torch.testing._internal.common_device_type import (
dtypes,
dtypesIfCUDA,
instantiate_device_type_tests,
onlyCPU,
onlyCUDA,
skipMeta,
)
from torch.testing._in... | 121,490 | 44.656144 | 130 | py |
pytorch | pytorch-main/test/test_matmul_cuda.py | # -*- coding: utf-8 -*-
# Owner(s): ["module: linear algebra"]
import unittest
from functools import partial
import torch
from torch.testing import make_tensor
from torch.testing._internal.common_cuda import SM53OrLater
from torch.testing._internal.common_device_type import (
dtypes,
instantiate_device_type_t... | 7,664 | 40.657609 | 104 | py |
pytorch | pytorch-main/test/test_logging.py | # Owner(s): ["module: unknown"]
import torch
from torch.testing._internal.common_utils import TestCase, run_tests
class LoggingTest(TestCase):
def testApiUsage(self):
"""
This test verifies that api usage logging is not triggered via static
initialization. Since it's triggered at first in... | 807 | 34.130435 | 114 | py |
pytorch | pytorch-main/test/test_sort_and_select.py | # Owner(s): ["module: tests"]
import torch
import numpy as np
import random
from torch import nan
from itertools import permutations, product
from torch.testing import make_tensor
from torch.testing._internal.common_dtype import all_types, all_types_and, floating_types_and, integral_types
from torch.testing._interna... | 52,100 | 45.066313 | 131 | py |
pytorch | pytorch-main/test/test_functionalization.py | # Owner(s): ["module: codegen"]
import torch
from contextlib import nullcontext
from torch.testing._internal.common_utils import (
TestCase, run_tests, skipIfTorchDynamo, TEST_WITH_TORCHDYNAMO, IS_WINDOWS,
xfail_inherited_tests
)
from torch.testing._internal.logging_tensor import LoggingTensor, capture_logs
fr... | 69,427 | 44.586343 | 198 | py |
pytorch | pytorch-main/test/test_masked.py | # Owner(s): ["module: masked operators"]
"""Tests for masked operations.
"""
import itertools
import torch
from typing import List, Any
from functools import wraps
import unittest
from torch.testing._internal.common_utils import skipIfTorchDynamo
from torch.testing._internal.common_utils import \
(TestCase, par... | 18,650 | 41.777523 | 131 | py |
pytorch | pytorch-main/test/test_decomp.py | # Owner(s): ["module: primTorch", "module: decompositions"]
from collections import defaultdict
from torch import Tensor
import torch.autograd
from torch._decomp import decomposition_table
from torch.utils._python_dispatch import TorchDispatchMode
from torch.utils._pytree import tree_map, tree_flatten, tree_unflatten... | 33,090 | 39.853086 | 127 | py |
pytorch | pytorch-main/test/test_functionalization_of_rng_ops.py | # Owner(s): ["oncall: pt2"]
import sys
import unittest
import torch
from torch.testing._internal.common_utils import (
TestCase,
run_tests,
)
from torch.testing._internal.common_device_type import instantiate_device_type_tests, dtypes
from functorch.compile import aot_function, nop, min_cut_rematerialization_p... | 11,571 | 31.968661 | 115 | py |
pytorch | pytorch-main/test/test_cpp_extensions_aot.py | # Owner(s): ["module: cpp-extensions"]
from itertools import repeat
import os
import re
from typing import Union, get_args, get_origin
import unittest
import torch.testing._internal.common_utils as common
from torch.testing._internal.common_utils import IS_WINDOWS, skipIfTorchDynamo
from torch.testing._internal.commo... | 13,935 | 38.256338 | 109 | py |
pytorch | pytorch-main/test/test_fx_reinplace_pass.py | # Owner(s): ["module: functionalization"]
import torch
from torch.testing._internal.common_utils import TestCase, run_tests
from torch.fx.passes.reinplace import reinplace
from torch.fx.experimental.proxy_tensor import make_fx
try:
from functorch.experimental import functionalize
HAS_FUNCTIONALIZATION = True
e... | 13,704 | 36.754821 | 108 | py |
pytorch | pytorch-main/test/test_cpp_extensions_open_device_registration.py | # Owner(s): ["module: cpp-extensions"]
import os
import shutil
import sys
from typing import Union
import tempfile
import unittest
import torch.testing._internal.common_utils as common
from torch.testing._internal.common_utils import IS_ARM64
import torch
import torch.utils.cpp_extension
from torch.utils.cpp_extensio... | 20,200 | 45.43908 | 126 | py |
pytorch | pytorch-main/test/test_legacy_vmap.py | # Owner(s): ["module: vmap"]
from torch.testing._internal.common_utils import TestCase, run_tests
import torch
import torch.nn.functional as F
from torch import Tensor
from torch._vmap_internals import vmap
import functools
import itertools
import warnings
from torch.testing._internal.common_device_type import instant... | 102,955 | 40.231878 | 115 | py |
pytorch | pytorch-main/test/test_stateless.py | # Owner(s): ["module: nn"]
import contextlib
import os
import re
import subprocess
import sys
import unittest
import torch
import torch.nn.utils.stateless as stateless
from torch.testing._internal.common_cuda import TEST_MULTIGPU
from torch.testing._internal.common_utils import run_tests, TestCase, parametrize, insta... | 37,109 | 39.870044 | 125 | py |
pytorch | pytorch-main/test/test_pruning_op.py | # Owner(s): ["module: unknown"]
import hypothesis.strategies as st
from hypothesis import given
import numpy as np
import torch
from torch.testing._internal.common_utils import TestCase, run_tests
import torch.testing._internal.hypothesis_utils as hu
hu.assert_deadline_disabled()
class PruningOpTest(TestCase):
... | 3,681 | 43.361446 | 108 | py |
pytorch | pytorch-main/test/test_hub.py | # Owner(s): ["module: hub"]
import unittest
from unittest.mock import patch
import os
import tempfile
import warnings
import torch
import torch.hub as hub
from torch.testing._internal.common_utils import retry, IS_SANDCASTLE, TestCase
def sum_of_state_dict(state_dict):
s = 0
for v in state_dict.values():
... | 11,304 | 42.314176 | 115 | py |
pytorch | pytorch-main/test/test_dispatch.py | # Owner(s): ["module: dispatch"]
import torch._C as C
from torch.testing._internal.common_utils import TestCase, run_tests
from torch._python_dispatcher import PythonDispatcher
from collections import namedtuple
import itertools
import os
import re
import torch.utils.cpp_extension
# TODO: Expand the dispatcher API t... | 41,564 | 42.342023 | 130 | py |
pytorch | pytorch-main/test/test_binary_ufuncs.py | # Owner(s): ["module: tests"]
import torch
import numpy as np
import itertools
from itertools import chain
from itertools import product
import math
import random
from numbers import Number
import warnings
import operator
from functools import partial
import torch.autograd.forward_ad as fwAD
from torch import inf, n... | 179,145 | 39.131272 | 131 | py |
pytorch | pytorch-main/test/test_cuda_sanitizer.py | # Owner(s): ["module: cuda"]
import sys
import textwrap
import traceback
from typing import List
import torch
import torch.cuda._sanitizer as csan
from torch.cuda._sanitizer import StreamId, DataPtr, EventId
from torch.testing._internal.common_utils import TestCase, run_tests, NoTest
# We cannot import TEST_CUDA fr... | 20,323 | 39.166008 | 102 | py |
pytorch | pytorch-main/test/test_overrides.py | # Owner(s): ["module: __torch_function__"]
import torch
import numpy as np
import inspect
import functools
import pprint
import pickle
import collections
import unittest
from torch.testing._internal.common_utils import TestCase, run_tests, TEST_WITH_CROSSREF
from torch.overrides import (
handle_torch_function,
... | 53,189 | 33.696673 | 114 | py |
pytorch | pytorch-main/test/test_namedtensor.py | # Owner(s): ["module: named tensor"]
import unittest
from torch.testing._internal.common_utils import TestCase, run_tests, TEST_NUMPY
from torch.testing._internal.common_cuda import TEST_CUDA
from torch.testing._internal.common_device_type import get_all_device_types
from collections import namedtuple, OrderedDict
imp... | 82,300 | 38.913191 | 124 | py |
pytorch | pytorch-main/test/test_fx_experimental.py | # Owner(s): ["module: fx"]
import math
import numbers
import operator
import pickle
import sys
import tempfile
import unittest
from types import BuiltinFunctionType
from typing import Callable, Dict, List, NamedTuple, Optional, Tuple, Union
import torch
import torch.fx.experimental.meta_tracer
import torch.fx.experim... | 62,779 | 36.480597 | 121 | py |
pytorch | pytorch-main/test/test_cpp_api_parity.py | # Owner(s): ["module: cpp"]
import torch
# NN tests use double as the default dtype
torch.set_default_dtype(torch.double)
import os
import torch.testing._internal.common_utils as common
import torch.testing._internal.common_nn as common_nn
from cpp_api_parity.parity_table_parser import parse_parity_tracker_table
fro... | 2,869 | 44.555556 | 103 | py |
pytorch | pytorch-main/test/test_functional_autograd_benchmark.py | # Owner(s): ["module: autograd"]
from torch.testing._internal.common_utils import TestCase, run_tests, slowTest, IS_WINDOWS
import subprocess
import tempfile
import os
import unittest
PYTORCH_COLLECT_COVERAGE = bool(os.environ.get("PYTORCH_COLLECT_COVERAGE"))
# This is a very simple smoke test for the functional au... | 2,574 | 39.234375 | 126 | py |
pytorch | pytorch-main/test/test_jit_fuser_te.py | # Owner(s): ["NNC"]
import operator
import os
import unittest
import contextlib
import math
import torch
import torch.nn.functional as F
from torch.testing import FileCheck
from typing import List
import warnings
# these needs to be set before `common_utils`
# infers `GRAPH_EXECUTOR`.
# this file **requires** these s... | 107,464 | 37.162287 | 123 | py |
pytorch | pytorch-main/test/test_monitor.py | # Owner(s): ["oncall: r2p"]
from torch.testing._internal.common_utils import (
TestCase, run_tests,
)
from datetime import timedelta, datetime
import tempfile
import time
from torch.monitor import (
Aggregation,
Event,
log_event,
register_event_handler,
unregister_event_handler,
Stat,
... | 4,481 | 27.367089 | 100 | py |
pytorch | pytorch-main/test/test_bundled_images.py | #!/usr/bin/env python3
# Owner(s): ["oncall: mobile"]
import torch
import torch.utils.bundled_inputs
import io
import cv2
from torch.testing._internal.common_utils import TestCase
torch.ops.load_library("//caffe2/torch/fb/operators:decode_bundled_image")
def model_size(sm):
buffer = io.BytesIO()
torch.jit.sa... | 3,081 | 36.585366 | 107 | py |
pytorch | pytorch-main/test/test_function_schema.py | # Owner(s): ["module: unknown"]
import torch
from torch.testing._internal.common_utils import TestCase, run_tests
from torch._C import parse_schema
class TestFunctionSchema(TestCase):
def test_serialize_and_deserialize(self):
schemas = torch._C._jit_get_all_schemas()
# so far we have around 1700 ... | 16,485 | 64.420635 | 132 | py |
pytorch | pytorch-main/test/test_cuda_expandable_segments.py | # Owner(s): ["module: cuda"]
# run time cuda tests, but with the allocator using expandable segments
import os
import torch
if torch.cuda.is_available():
torch.cuda.memory._set_allocator_settings('expandable_segments:True')
current_dir = os.path.dirname(os.path.abspath(__file__))
filepath = os.path.join(current_... | 406 | 30.307692 | 73 | py |
pytorch | pytorch-main/test/test_foreach.py | # Owner(s): ["module: mta"]
from contextlib import nullcontext
from numbers import Number
import random
import re
import torch
import unittest
import itertools
from torch.testing import make_tensor
from torch.testing._comparison import default_tolerances
from torch.testing._internal.common_utils import \
TestCase... | 51,291 | 49.187867 | 130 | py |
pytorch | pytorch-main/test/test_fake_tensor.py | # Owner(s): ["module: meta tensors"]
from torch.testing._internal.common_utils import (
TestCase, run_tests, skipIfCrossRef, skipIfRocm, skipIfTorchDynamo, parametrize,
instantiate_parametrized_tests)
import torch
import torch._dynamo
import itertools
import numpy as np
from torch.testing._internal.jit_utils i... | 43,472 | 37.335979 | 121 | py |
pytorch | pytorch-main/test/test_dynamic_shapes.py | # -*- coding: utf-8 -*-
# Owner(s): ["oncall: jit"]
import contextlib
import copy
import itertools
import inspect
import math
import operator
import re
import sympy
import torch
import torch.fx
import torch.nn.functional as F
from torch import sym_int, SymBool, SymFloat, SymInt
from torch._C import _disabled_torch_fu... | 64,533 | 34.264481 | 138 | py |
pytorch | pytorch-main/test/test_segment_reductions.py | # Owner(s): ["module: scatter & gather ops"]
from itertools import product
from functools import partial
import numpy as np
import torch
from torch.testing._internal.common_device_type import (
instantiate_device_type_tests,
dtypes,
)
from torch.testing._internal.common_utils import (
TestCase,
run_te... | 23,285 | 39.287197 | 118 | py |
pytorch | pytorch-main/test/_test_bazel.py | # Owner(s): ["module: bazel"]
"""
This test module contains a minimalistic "smoke tests" for the bazel build.
Currently it doesn't use any testing framework (i.e. pytest)
TODO: integrate this into the existing pytorch testing framework.
The name uses underscore `_test_bazel.py` to avoid globbing into other non-bazel... | 894 | 27.870968 | 107 | py |
pytorch | pytorch-main/test/test_comparison_utils.py | #!/usr/bin/env python3
# Owner(s): ["module: internals"]
import torch
from torch.testing._internal.common_utils import TestCase, run_tests
class TestComparisonUtils(TestCase):
def test_all_equal_no_assert(self):
t = torch.tensor([0.5])
torch._assert_tensor_metadata(t, [1], [1], torch.float)
d... | 1,045 | 27.27027 | 69 | py |
pytorch | pytorch-main/test/test_module_init.py | # Owner(s): ["module: nn"]
import inspect
import torch
from unittest import mock
from unittest.mock import MagicMock, patch
from torch.testing._internal.common_dtype import floating_types
from torch.testing._internal.common_device_type import instantiate_device_type_tests, dtypes
from torch.testing._internal.common_qu... | 24,936 | 45.437616 | 112 | py |
pytorch | pytorch-main/test/test_mkl_verbose.py | # Owner(s): ["module: unknown"]
from torch.testing._internal.common_utils import TestCase, run_tests
import os
import subprocess
import sys
class TestMKLVerbose(TestCase):
def test_verbose_on(self):
num = 0
loc = os.path.dirname(os.path.abspath(__file__))
with subprocess.Popen(f'{sys.execu... | 1,464 | 40.857143 | 115 | py |
pytorch | pytorch-main/test/test_prims.py | # Owner(s): ["module: primTorch"]
from functools import partial
from itertools import product
import warnings
from warnings import catch_warnings
import unittest
import torch
from torch.testing import make_tensor
from torch.testing._internal.common_utils import (parametrize, run_tests, TestCase, TEST_SCIPY,
... | 52,009 | 38.075883 | 116 | py |
pytorch | pytorch-main/test/test_proxy_tensor.py | # Owner(s): ["module: ProxyTensor"]
from torch.testing._internal.common_utils import TestCase, run_tests, xfail_inherited_tests
import torch
import unittest
import warnings
import operator
from collections.abc import Iterable
from torch.testing._internal.common_device_type import instantiate_device_type_tests
from tor... | 65,996 | 38.781193 | 221 | py |
pytorch | pytorch-main/test/test_quantization.py | # -*- coding: utf-8 -*-
# Owner(s): ["oncall: quantization"]
import logging
from torch.testing._internal.common_utils import run_tests
# Quantization core tests. These include tests for
# - quantized kernels
# - quantized functional operators
# - quantized workflow modules
# - quantized workflow operators
# - quantiz... | 8,685 | 54.679487 | 112 | py |
pytorch | pytorch-main/test/test_determination.py | # Owner(s): ["module: ci"]
import os
import run_test
from torch.testing._internal.common_utils import TestCase, run_tests
class DummyOptions:
verbose = False
class DeterminationTest(TestCase):
# Test determination on a subset of tests
TESTS = [
"test_nn",
"test_jit_profiling",
... | 4,556 | 32.021739 | 102 | py |
pytorch | pytorch-main/test/test_public_bindings.py | # -*- coding: utf-8 -*-
# Owner(s): ["module: autograd"]
from torch.testing._internal.common_utils import TestCase, run_tests, IS_JETSON, IS_WINDOWS
import pkgutil
import torch
import sys
from typing import Callable
import inspect
import json
import os
import unittest
# TODO(jansel): we should remove this workaround... | 15,150 | 41.203343 | 119 | py |
pytorch | pytorch-main/test/test_schema_check.py | # Owner(s): ["oncall: jit"]
import os
import sys
import torch
from torch.utils._pytree import tree_map
import unittest
from torch.testing._internal.common_utils import run_tests
from torch.fx.operator_schemas import normalize_function
from torch._subclasses.schema_check_mode import SchemaCheckMode
from torch.utils._p... | 21,690 | 41.698819 | 116 | py |
pytorch | pytorch-main/test/test_jit_autocast.py | # Owner(s): ["oncall: jit"]
import torch
from torch.cuda.amp import autocast
from typing import Optional, Tuple
import unittest
from test_jit import JitTestCase
from torch.testing._internal.common_cuda import TEST_CUDA
from torch.testing._internal.common_utils import run_tests, skipIfTorchDynamo
from torch.testing im... | 36,464 | 37.669141 | 117 | py |
pytorch | pytorch-main/test/test_modules.py | # Owner(s): ["module: nn"]
from itertools import product
from inspect import signature, isgenerator
from copy import deepcopy
import tempfile
from operator import methodcaller
import torch
from torch.testing._internal.common_cuda import with_tf32_off
from torch.testing._internal.common_device_type import (
instan... | 37,694 | 49.870445 | 131 | py |
pytorch | pytorch-main/test/create_dummy_torchscript_model.py | # Usage: python create_dummy_model.py <name_of_the_file>
import sys
import torch
from torch import nn
class NeuralNetwork(nn.Module):
def __init__(self):
super().__init__()
self.flatten = nn.Flatten()
self.linear_relu_stack = nn.Sequential(
nn.Linear(28 * 28, 512),
... | 892 | 23.135135 | 56 | py |
pytorch | pytorch-main/test/test_autocast.py | # Owner(s): ["module: unknown"]
import collections
import unittest
import torch
from torch.testing._internal.common_utils import TestCase, run_tests, IS_WINDOWS
from torch.testing._internal.autocast_test_lists import AutocastCPUTestLists
from torch.utils._python_dispatch import TorchDispatchMode
class TestAutocastCP... | 10,556 | 42.089796 | 113 | py |
pytorch | pytorch-main/test/simulate_nccl_errors.py |
import torch.distributed as c10d
import torch
import argparse
import os
import logging
logging.basicConfig(format='%(asctime)s - %(name)s - %(levelname)s - %(message)s', level=logging.INFO)
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description='Simple script to simulate NCCL errors. The... | 1,628 | 41.868421 | 102 | py |
pytorch | pytorch-main/test/test_datapipe.py | # Owner(s): ["module: dataloader"]
import copy
import itertools
import os
import os.path
import pickle
import pydoc
import random
import sys
import tempfile
import warnings
from functools import partial
from typing import (
Any,
Awaitable,
Dict,
Generic,
Iterator,
List,
Optional,
Set,
... | 144,393 | 39.720248 | 122 | py |
pytorch | pytorch-main/test/test_tensorexpr_pybind.py | # Owner(s): ["NNC"]
import torch
import numpy as np
import torch._C._te as te
from torch.testing._internal.common_utils import run_tests
from torch.testing._internal.jit_utils import JitTestCase
import unittest
LLVM_ENABLED = torch._C._llvm_enabled()
def construct_adder(n: int, dtype=torch.float32):
A = te.Buf... | 16,471 | 34.196581 | 109 | py |
pytorch | pytorch-main/test/test_itt.py | # Owner(s): ["module: intel"]
import torch
import unittest
from torch.testing._internal.common_utils import TestCase, run_tests, load_tests
# load_tests from common_utils is used to automatically filter tests for
# sharding on sandcastle. This line silences flake warnings
load_tests = load_tests
@unittest.skipIf(not... | 641 | 29.571429 | 80 | py |
pytorch | pytorch-main/test/test_show_pickle.py | # Owner(s): ["oncall: mobile"]
import unittest
import io
import tempfile
import torch
import torch.utils.show_pickle
from torch.testing._internal.common_utils import TestCase, run_tests, IS_WINDOWS
class TestShowPickle(TestCase):
@unittest.skipIf(IS_WINDOWS, "Can't re-open temp file on Windows")
def test_sc... | 1,052 | 27.459459 | 91 | py |
pytorch | pytorch-main/test/test_mkldnn_verbose.py | # Owner(s): ["module: unknown"]
from torch.testing._internal.common_utils import TestCase, run_tests
import os
import subprocess
import sys
class TestMKLDNNVerbose(TestCase):
def test_verbose_on(self):
num = 0
loc = os.path.dirname(os.path.abspath(__file__))
with subprocess.Popen(f'{sys.ex... | 1,482 | 41.371429 | 118 | py |
pytorch | pytorch-main/test/test_package.py | # Owner(s): ["oncall: package/deploy"]
from package.test_resources import TestResources # noqa: F401
from package.test_model import ModelTest # noqa: F401
from package.test_dependency_api import TestDependencyAPI # noqa: F401
from package.test_mangling import TestMangling # noqa: F401
from package.test_misc import... | 1,353 | 51.076923 | 97 | py |
pytorch | pytorch-main/test/test_type_hints.py | # Owner(s): ["module: typing"]
import unittest
from torch.testing._internal.common_utils import TestCase, run_tests, set_cwd
import tempfile
import torch
import doctest
import os
import inspect
from pathlib import Path
try:
import mypy.api
HAVE_MYPY = True
except ImportError:
HAVE_MYPY = False
def get_e... | 5,064 | 35.438849 | 94 | py |
pytorch | pytorch-main/test/test_sympy_utils.py | # -*- coding: utf-8 -*-
# Owner(s): ["oncall: pt2"]
import itertools
import sys
import sympy
from torch.testing._internal.common_utils import (
instantiate_parametrized_tests,
parametrize,
run_tests,
TestCase,
)
from torch.utils._sympy.value_ranges import ValueRangeAnalysis, ValueRanges
from torch.uti... | 10,038 | 34.725979 | 112 | py |
pytorch | pytorch-main/test/test_futures.py | # Owner(s): ["module: unknown"]
import threading
import time
import torch
import unittest
from torch.futures import Future
from torch.testing._internal.common_utils import IS_WINDOWS, TestCase, TemporaryFileName, run_tests
from typing import TypeVar
T = TypeVar("T")
def add_one(fut):
return fut.wait() + 1
cla... | 10,488 | 29.759531 | 99 | py |
pytorch | pytorch-main/test/load_torchscript_model.py | import sys
import torch
if __name__ == '__main__':
script_mod = torch.jit.load(sys.argv[1])
mod = torch.load(sys.argv[1] + ".orig")
print(script_mod)
inp = torch.rand(2, 28 * 28)
_ = mod(inp)
sys.exit(0)
| 229 | 19.909091 | 44 | py |
pytorch | pytorch-main/test/test_meta.py | # Owner(s): ["module: primTorch"]
import itertools
import torch
import os
from enum import Enum
from torch.overrides import resolve_name
from torch.utils._pytree import tree_map, tree_flatten, tree_unflatten
from torch._subclasses.meta_utils import MetaConverter, assert_metadata_eq
import torch.utils._python_dispatch
... | 53,095 | 38.012491 | 132 | py |
pytorch | pytorch-main/test/test_metal.py | # Owner(s): ["oncall: mobile"]
import torch
from torch.nn import functional as F
from torch.testing._internal.common_utils import TestCase, run_tests
from torch.testing import FileCheck
import io
class TestMetalRewritePass(TestCase):
@staticmethod
def validate_transformed_module(
# To please flak... | 6,650 | 40.055556 | 105 | py |
pytorch | pytorch-main/test/test_jit.py | # -*- coding: utf-8 -*-
# Owner(s): ["oncall: jit"]
import torch
# This is how we include tests located in test/jit/...
# They are included here so that they are invoked when you call `test_jit.py`,
# do not run these test files directly.
from jit.test_tracer import TestTracer, TestMixTracingScripting # noqa: F401
f... | 574,650 | 34.345737 | 132 | py |
pytorch | pytorch-main/test/test_dlpack.py | # -*- coding: utf-8 -*-
# Owner(s): ["module: tests"]
import torch
from torch.testing import make_tensor
from torch.testing._internal.common_utils import TestCase, run_tests, IS_JETSON
from torch.testing._internal.common_device_type import (
instantiate_device_type_tests, onlyCUDA, dtypes, skipMeta, skipCUDAIfRocm... | 7,928 | 35.539171 | 83 | py |
pytorch | pytorch-main/test/test_torch.py | # -*- coding: utf-8 -*-
# Owner(s): ["module: tests"]
import torch
import torch.utils.data
import numpy as np
import contextlib
import gc
import io
import inspect
import itertools
import math
import random
import re
import copy
import os
import tempfile
import unittest
import warnings
import types
import pickle
impor... | 411,053 | 43.409464 | 132 | py |
pytorch | pytorch-main/test/test_complex.py | # Owner(s): ["module: complex"]
import torch
from torch.testing._internal.common_device_type import (
instantiate_device_type_tests,
dtypes,
onlyCPU,
)
from torch.testing._internal.common_utils import TestCase, run_tests
from torch.testing._internal.common_dtype import complex_types
devices = (torch.devic... | 9,347 | 53.348837 | 131 | py |
pytorch | pytorch-main/test/test_jit_string.py | # Owner(s): ["oncall: jit"]
from test_jit import JitTestCase
from torch.testing._internal.common_utils import run_tests
from typing import List, Tuple
class TestScript(JitTestCase):
def test_str_ops(self):
def test_str_is(s: str) -> Tuple[bool, bool, bool, bool, bool, bool, bool, bool, bool, bool, bool]:... | 13,131 | 38.317365 | 123 | py |
pytorch | pytorch-main/test/run_test.py | #!/usr/bin/env python3
import argparse
import copy
import glob
import json
import os
import pathlib
import shutil
import signal
import subprocess
import sys
import tempfile
from datetime import datetime
from distutils.version import LooseVersion
from typing import Any, cast, Dict, List, Optional, Union
import pkg_res... | 60,191 | 34.743468 | 127 | py |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.