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/scripts/release_notes/namespace_check.py | import argparse
import torch
from os import path
import json
# Import all utils so that getattr below can find them
from torch.utils import bottleneck, checkpoint, model_zoo
all_submod_list = [
"",
"nn",
"nn.functional",
"nn.init",
"optim",
"autograd",
"cuda",
"sparse",
"distributi... | 3,186 | 26.008475 | 106 | py |
pytorch | pytorch-main/scripts/release_notes/classifier.py | import argparse
from pathlib import Path
import torch
import torchtext
from torchtext.functional import to_tensor
import torch.nn as nn
import torch.nn.functional as F
from typing import List, Dict
import pandas as pd
from dataclasses import dataclass
import math
import pickle
import random
from tqdm import tqdm
from i... | 14,504 | 39.51676 | 147 | py |
pytorch | pytorch-main/scripts/release_notes/categorize.py | import argparse
import os
import textwrap
from common import topics, get_commit_data_cache
from commitlist import CommitList
# Imports for working with classi
from classifier import CommitClassifier, CategoryConfig, XLMR_BASE, get_author_map, get_file_map, CommitClassifierInputs
import common
import torch
from pathlib... | 6,818 | 37.965714 | 133 | py |
pytorch | pytorch-main/scripts/release_notes/commitlist.py | import argparse
from common import run, topics, get_features, frontend_categories
from collections import defaultdict
import os
from pathlib import Path
import csv
import pprint
import common
from common import get_commit_data_cache, features_to_dict
import re
import dataclasses
from typing import List
"""
Example Us... | 19,929 | 41.58547 | 421 | py |
pytorch | pytorch-main/scripts/release_notes/common.py | from collections import namedtuple
from pathlib import Path
import locale
import subprocess
import re
import requests
import os
import json
from dataclasses import dataclass
@dataclass
class CategoryGroup:
name: str
categories: list
frontend_categories = [
'meta',
'nn',
'linalg',
'cpp',
'p... | 7,519 | 23.900662 | 132 | py |
pytorch | pytorch-main/scripts/jit/log_extract.py | import argparse
import functools
import traceback
from torch.utils.jit.log_extract import extract_ir, load_graph_and_inputs, run_baseline_no_fusion, run_nnc, run_nvfuser
from typing import List, Tuple, Callable, Optional
'''
Usage:
1. Run your script and pipe into a log file
PYTORCH_JIT_LOG_LEVEL=">>graph_fuser" pyt... | 4,135 | 38.390476 | 130 | py |
pytorch | pytorch-main/android/pytorch_android/generate_test_torchscripts.py | import torch
from torch import Tensor
from typing import Dict, List, Tuple, Optional
OUTPUT_DIR = "src/androidTest/assets/"
def scriptAndSave(module, fileName):
print('-' * 80)
script_module = torch.jit.script(module)
print(script_module.graph)
outputFileName = OUTPUT_DIR + fileName
# note that th... | 3,906 | 27.727941 | 102 | py |
pytorch | pytorch-main/android/test_app/make_assets.py | import torch
import torchvision
print(torch.version.__version__)
resnet18 = torchvision.models.resnet18(pretrained=True)
resnet18.eval()
resnet18_traced = torch.jit.trace(resnet18, torch.rand(1, 3, 224, 224)).save("app/src/main/assets/resnet18.pt")
resnet50 = torchvision.models.resnet50(pretrained=True)
resnet50.eva... | 629 | 36.058824 | 111 | py |
pytorch | pytorch-main/android/test_app/make_assets_custom.py | """
This is a script for PyTorch Android custom selective build test. It prepares
MobileNetV2 TorchScript model, and dumps root ops used by the model for custom
build script to create a tailored build which only contains these used ops.
"""
import torch
import torchvision
import yaml
# Download and trace the model.
m... | 806 | 30.038462 | 78 | py |
pytorch | pytorch-main/.ci/pytorch/perf_test/compare_with_baseline.py | import sys
import json
import math
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('--test-name', dest='test_name', action='store',
required=True, help='test name')
parser.add_argument('--sample-stats', dest='sample_stats', action='store',
required=True, h... | 2,571 | 31.15 | 78 | py |
pytorch | pytorch-main/.ci/pytorch/win-test-helpers/run_python_nn_smoketests.py | #!/usr/bin/env python3
import subprocess
import os
COMMON_TESTS = [
(
"Checking that torch is available",
"import torch",
),
(
"Checking that MKL is available",
"import torch; exit(0 if torch.backends.mkl.is_available() else 1)",
),
]
GPU_TESTS = [
(
"Check... | 1,760 | 30.446429 | 99 | py |
pytorch | pytorch-main/docs/caffe2/process.py | #!/usr/bin/env python3
## @package process
# Module doxygen.process
# Script to insert preamble for doxygen and regen API docs
import os
import shutil
# Module caffe2...caffe2.python.control_test
def insert(originalfile, first_line, description):
with open(originalfile, 'r') as f:
f1 = f.readline()
... | 2,022 | 34.491228 | 99 | py |
pytorch | pytorch-main/docs/cpp/source/conf.py | # -*- coding: utf-8 -*-
#
# PyTorch documentation build configuration file, created by
# sphinx-quickstart on Fri Dec 23 13:31:47 2016.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# A... | 9,310 | 35.089147 | 83 | py |
pytorch | pytorch-main/docs/source/conf.py | # -*- coding: utf-8 -*-
#
# PyTorch documentation build configuration file, created by
# sphinx-quickstart on Fri Dec 23 13:31:47 2016.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# A... | 23,143 | 29.293194 | 109 | py |
pytorch | pytorch-main/docs/source/scripts/build_opsets.py | import os
from pathlib import Path
import torch
from collections import OrderedDict
from torchgen.gen import parse_native_yaml
import torch._prims as prims
ROOT = Path(__file__).absolute().parent.parent.parent.parent
NATIVE_FUNCTION_YAML_PATH = ROOT / Path("aten/src/ATen/native/native_functions.yaml")
TAGS_YAML_PATH ... | 2,071 | 26.626667 | 85 | py |
pytorch | pytorch-main/docs/source/scripts/build_activation_images.py | """
This script will generate input-out plots for all of the activation
functions. These are for use in the documentation, and potentially in
online tutorials.
"""
from pathlib import Path
import torch
import matplotlib
from matplotlib import pyplot as plt
matplotlib.use("Agg")
# Create a directory for the images,... | 2,109 | 25.375 | 78 | py |
pytorch | pytorch-main/docs/source/scripts/build_quantization_configs.py | """
This script will generate default values of quantization configs.
These are for use in the documentation.
"""
import torch
from torch.ao.quantization.backend_config import get_native_backend_config_dict
from torch.ao.quantization.backend_config.utils import (
entry_to_pretty_str,
remove_boolean_dispatch_fr... | 1,920 | 29.492063 | 96 | py |
pytorch | pytorch-main/docs/source/scripts/exportdb/generate_example_rst.py | import inspect
import os
import re
from pathlib import Path
import torch
import torch._dynamo as torchdynamo
from torch._export import export
from torch._export.db.case import ExportCase, normalize_inputs
from torch._export.db.examples import all_examples
PWD = Path(__file__).absolute().parent
ROOT = Path(__file__)... | 4,512 | 24.788571 | 96 | py |
pytorch | pytorch-main/docs/source/scripts/onnx/build_onnx_diagnostics_rules_md.py | import argparse
import os
from dataclasses import fields
from torch.onnx._internal import diagnostics
from torch.onnx._internal.diagnostics import infra
def gen_docs(out_dir: str):
os.makedirs(out_dir, exist_ok=True)
for field in fields(diagnostics.rules):
rule = getattr(diagnostics.rules, field.name... | 1,115 | 28.368421 | 78 | py |
pytorch | pytorch-main/docs/source/scripts/onnx/build_onnx_supported_aten_op_csv_table.py | """
This script generates a CSV table with all ATen operators
supported by `torch.onnx.export`. The generated table is included by
docs/source/onnx_supported_aten_list.rst.
"""
import os
from torch.onnx import _onnx_supported_ops
# Constants
BUILD_DIR = "build/onnx"
SUPPORTED_OPS_CSV_FILE = "auto_gen_supported_op_lis... | 1,989 | 27.84058 | 75 | py |
pytorch | pytorch-main/aten/src/ATen/native/quantized/cpu/qnnpack/configure.py | #!/usr/bin/env python3
#
# 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 confu
from confu import arm, x86
parser = confu.standard_parser()
def main(ar... | 12,127 | 41.554386 | 82 | py |
pytorch | pytorch-main/functorch/__init__.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
# Top-level APIs. Please think carefully before adding something to the
# top-level namespace:
# - p... | 996 | 33.37931 | 81 | py |
pytorch | pytorch-main/functorch/_src/aot_autograd/__init__.py | # This file has moved to under torch/_functorch. It is not public API.
# If you are not a PyTorch developer and you are relying on the following
# imports, please file an issue.
from torch._functorch.aot_autograd import (
aot_autograd_decompositions,
KNOWN_TYPES,
PytreeThunk,
)
| 291 | 31.444444 | 73 | py |
pytorch | pytorch-main/functorch/_src/vmap/__init__.py | # This file has moved to under torch/_functorch. It is not public API.
# If you are not a PyTorch developer and you are relying on the following
# imports, please file an issue.
from torch._functorch.vmap import (
_add_batch_dim,
_broadcast_to_and_flatten,
_get_name,
_remove_batch_dim,
_validate_and... | 467 | 26.529412 | 73 | py |
pytorch | pytorch-main/functorch/_src/make_functional/__init__.py | # This file has moved to under torch/_functorch. It is not public API.
# If you are not a PyTorch developer and you are relying on the following
# imports, please file an issue.
from torch._functorch.make_functional import _swap_state
| 235 | 46.2 | 73 | py |
pytorch | pytorch-main/functorch/_src/eager_transforms/__init__.py | # This file has moved to under torch/_functorch. It is not public API.
# If you are not a PyTorch developer and you are relying on the following
# imports, please file an issue.
from torch._functorch.eager_transforms import (
_unwrap_functional_tensor,
_assert_wrapped_functional,
)
| 291 | 35.5 | 73 | py |
pytorch | pytorch-main/functorch/dim/batch_tensor.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.
from torch._C._functorch import (
_vmap_add_layers,
_vmap_remove_layers,
)
from contextlib import context... | 678 | 24.148148 | 78 | py |
pytorch | pytorch-main/functorch/dim/tree_map.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.
from functorch._C import dim
tree_flatten = dim.tree_flatten
def tree_map(fn, tree):
vs, unflatten = tree_fl... | 372 | 27.692308 | 71 | py |
pytorch | pytorch-main/functorch/dim/wrap_type.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.
from types import FunctionType, BuiltinMethodType, MethodDescriptorType, WrapperDescriptorType, GetSetDescriptorT... | 1,697 | 32.96 | 118 | py |
pytorch | pytorch-main/functorch/dim/op_properties.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
# pointwise operators can go through a faster pathway
tensor_magic_methods = [
'add',
''
]
p... | 6,568 | 22.212014 | 77 | py |
pytorch | pytorch-main/functorch/dim/__init__.py | import torch
from typing import Union, Sequence
import inspect
import dis
from .tree_map import tree_flatten, tree_map
from .wrap_type import wrap_type
import functorch._C
from functorch._C import dim as _C
_C._patch_tensor_class()
dims, DimList, dimlists = _C.dims, _C.DimList, _C.dimlists
class DimensionMismatchError... | 4,711 | 26.395349 | 129 | py |
pytorch | pytorch-main/functorch/dim/delayed_mul_tensor.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 . import _Tensor, Tensor
from .reference import _dims, _enable_layers, llist, ltuple
class Dela... | 2,338 | 33.397059 | 96 | py |
pytorch | pytorch-main/functorch/dim/reference.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.
# reference python implementations for C ops
import torch
from .tree_map import tree_flatten, tree_map
from .batc... | 19,731 | 34.362007 | 128 | py |
pytorch | pytorch-main/functorch/benchmarks/chrome_trace_parser.py | #!/usr/bin/env python3
import argparse
import os
import logging
import pandas as pd
from torch._functorch.benchmark_utils import compute_utilization
# process the chrome traces output by the pytorch profiler
# require the json input file's name to be in format {model_name}_chrome_trace_*.json
# the runtimes file sho... | 2,192 | 30.782609 | 91 | py |
pytorch | pytorch-main/functorch/benchmarks/pointwise_scorecard.py | import sys
import time
import torch
import inspect
import itertools
from functorch import pointwise_operator
torch.set_num_threads(1)
torch._C._debug_set_fusion_group_inlining(False)
def rand(*shape):
return torch.rand(*shape).mul(16).add(1)
# -------------------------------------------------------------------... | 5,939 | 24.826087 | 116 | py |
pytorch | pytorch-main/functorch/benchmarks/cse.py | import torch
import torch.fx as fx
from functorch import make_fx
from torch.profiler import profile, ProfilerActivity
from torch._functorch.compile_utils import fx_graph_cse
def profile_it(f, inp):
for _ in range(5):
f(inp)
itr = 5
with profile(activities=[ProfilerActivity.CUDA], record_shapes=Tr... | 2,399 | 22.076923 | 104 | py |
pytorch | pytorch-main/functorch/benchmarks/per_sample_grads.py | import torch
import torch.nn as nn
import torchvision.models as models
from opacus.utils.module_modification import convert_batchnorm_modules
import time
from functorch import vmap, grad
from functorch import make_functional
from opacus import PrivacyEngine
device = 'cuda'
batch_size = 128
torch.manual_seed(0)
model... | 2,703 | 27.765957 | 77 | py |
pytorch | pytorch-main/functorch/benchmarks/operator_authoring.py | from functools import partial
import numpy as np
import pandas as pd
import timeit
import torch
from functorch.compile import pointwise_operator
WRITE_CSV = False
CUDA = False
SIZES = [1, 512, 8192]
NUMBER = [100, 10, 1, 1]
REPEAT = 20
@pointwise_operator
def nnc_add(a, b):
return a + b
@pointwise_operator
def... | 7,616 | 28.183908 | 88 | py |
pytorch | pytorch-main/functorch/examples/compilation/eager_fusion.py | from functorch.compile import aot_function, tvm_compile
import torch
import time
import torch.utils
a = torch.randn(2000, 1, 4, requires_grad=True)
b = torch.randn(1, 2000, 4)
def f(a):
return (a * b).sum(dim=0)
fw_compiler = tvm_compile(target='llvm', tuning_logfile='fw_keops')
bw_compiler = tvm_compile(targe... | 1,164 | 20.181818 | 67 | py |
pytorch | pytorch-main/functorch/examples/compilation/simple_function.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.
from functorch import grad, make_fx
from functorch.compile import nnc_jit
import torch
import time
def f(x):
... | 760 | 20.742857 | 71 | py |
pytorch | pytorch-main/functorch/examples/compilation/fuse_module.py | import timeit
from functorch.compile import compiled_module, tvm_compile
import torch.nn as nn
import torch
def nop(f, _):
return f
fw_compiler = tvm_compile(target='llvm', tuning_logfile='fw_keops')
bw_compiler = tvm_compile(target='llvm', tuning_logfile='bw_keops')
fw_compiler = nop
bw_compiler = nop
def ru... | 1,438 | 24.696429 | 76 | py |
pytorch | pytorch-main/functorch/examples/compilation/linear_train.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.
from functorch import make_functional
from functorch.compile import nnc_jit
import torch
import torch.nn as nn
im... | 2,147 | 22.604396 | 93 | py |
pytorch | pytorch-main/functorch/examples/dp_cifar10/cifar10_transforms.py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
"""
Runs CIFAR10 training with differential privacy.
"""
import argparse
import logging
import shutil
import sys
from datetime import datetime, timedelta
import numpy as np
import torch
import torch.nn as nn
import torch.op... | 14,965 | 29.356998 | 155 | py |
pytorch | pytorch-main/functorch/examples/dp_cifar10/cifar10_opacus.py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
"""
Runs CIFAR10 training with differential privacy.
"""
import argparse
import logging
import shutil
import sys
from datetime import datetime, timedelta
import numpy as np
import torch
import torch.nn as nn
import torch.op... | 13,432 | 27.580851 | 155 | py |
pytorch | pytorch-main/functorch/examples/lennard_jones/lennard_jones.py | # This example was adapated from https://github.com/muhrin/milad
# It is licensed under the GLPv3 license. You can find a copy of it
# here: https://www.gnu.org/licenses/gpl-3.0.en.html .
import torch
from torch import nn
from torch.nn.functional import mse_loss
from torch.func import jacrev, vmap
sigma = 0.5
epsilon... | 2,016 | 27.408451 | 102 | py |
pytorch | pytorch-main/functorch/examples/maml_omniglot/maml-omniglot-transforms.py | #!/usr/bin/env python3
#
# Copyright (c) Facebook, Inc. and its affiliates.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | 8,801 | 33.249027 | 109 | py |
pytorch | pytorch-main/functorch/examples/maml_omniglot/maml-omniglot-ptonly.py | #!/usr/bin/env python3
#
# Copyright (c) Facebook, Inc. and its affiliates.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | 9,262 | 34.087121 | 109 | py |
pytorch | pytorch-main/functorch/examples/maml_omniglot/maml-omniglot-higher.py | #!/usr/bin/env python3
#
# Copyright (c) Facebook, Inc. and its affiliates.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | 9,516 | 34.248148 | 109 | py |
pytorch | pytorch-main/functorch/examples/maml_omniglot/support/omniglot_loaders.py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ... | 11,730 | 37.716172 | 116 | py |
pytorch | pytorch-main/functorch/examples/ensembling/parallel_train.py | import argparse
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.func import functional_call, grad_and_value, vmap, stack_module_state
# Adapted from http://willwhitney.com/parallel-training-jax.html , which is a
# tutorial on Model Ensembling with JAX by Will Whitney.
#
# The ... | 4,727 | 32.295775 | 91 | py |
pytorch | pytorch-main/functorch/examples/maml_regression/evjang_transforms.py | # Eric Jang originally wrote an implementation of MAML in JAX
# (https://github.com/ericjang/maml-jax).
# We translated his implementation from JAX to PyTorch.
from torch.func import grad, vmap
import matplotlib.pyplot as plt
import math
import torch
import numpy as np
from torch.nn import functional as F
import matpl... | 3,494 | 25.884615 | 92 | py |
pytorch | pytorch-main/functorch/examples/maml_regression/evjang_transforms_module.py | # Eric Jang originally wrote an implementation of MAML in JAX
# (https://github.com/ericjang/maml-jax).
# We translated his implementation from JAX to PyTorch.
from functorch import grad, vmap, make_functional
import matplotlib.pyplot as plt
import math
import torch
import numpy as np
from torch import nn
from torch.n... | 3,394 | 25.732283 | 87 | py |
pytorch | pytorch-main/functorch/examples/maml_regression/evjang.py | # Eric Jang originally wrote an implementation of MAML in JAX
# (https://github.com/ericjang/maml-jax).
# We translated his implementation from JAX to PyTorch.
import matplotlib.pyplot as plt
import math
import torch
import numpy as np
from torch.nn import functional as F
import matplotlib as mpl
mpl.use('Agg')
def ... | 3,571 | 28.04065 | 112 | py |
pytorch | pytorch-main/functorch/op_analysis/gen_data.py | import yaml
import csv
import torch
from collections import defaultdict
def get_ops_for_key(key):
# Needs modified PyTorch C++ code to work
if key is None:
ops = torch._C._dispatch_get_registrations_for_dispatch_key()
else:
ops = torch._C._dispatch_get_registrations_for_dispatch_key(key)
... | 5,536 | 34.044304 | 122 | py |
pytorch | pytorch-main/functorch/docs/source/conf.py | # -*- coding: utf-8 -*-
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# All configuration values have a default; values that are commented out
# serve to show the default.
# If extensi... | 10,837 | 31.449102 | 92 | py |
pytorch | pytorch-main/functorch/compile/__init__.py | from torch._functorch.python_key import pythonkey_decompose
from torch._functorch.fx_minifier import minifier
from torch._functorch.aot_autograd import (
aot_function,
aot_module,
compiled_function,
compiled_module,
aot_module_simplified,
get_graph_being_compiled,
get_aot_graph_name,
get... | 776 | 23.28125 | 59 | py |
pytorch | pytorch-main/functorch/einops/rearrange.py | from __future__ import annotations
import functools
from typing import Callable, Dict, List, Sequence, Tuple, Union
import torch
from functorch._C import dim as _C
from ._parsing import AnonymousAxis, _ellipsis, comma_separate, parse_pattern, validate_rearrange_expressions
__all__ = ["rearrange"]
dims = _C.dims
@... | 7,811 | 41.227027 | 120 | py |
pytorch | pytorch-main/functorch/experimental/_cond.py | from dataclasses import dataclass
import torch
from torch.multiprocessing.reductions import StorageWeakRef
import torch.utils._pytree as pytree
from torch._C import DispatchKey, DispatchKeySet, _ExcludeDispatchKeyGuard
from torch._functorch.eager_transforms import _unwrap_all_tensors_from_functional, _wrap_all_tensor... | 13,088 | 39.903125 | 129 | py |
pytorch | pytorch-main/functorch/experimental/_map.py | import torch
import torch.utils._pytree as pytree
from torch._C import DispatchKey, DispatchKeySet, _ExcludeDispatchKeyGuard
from torch._functorch.eager_transforms import _unwrap_all_tensors_from_functional, _wrap_all_tensors_to_functional, functionalize
from torch._functorch.aot_autograd import create_joint, AOTConfig... | 14,049 | 42.63354 | 129 | py |
pytorch | pytorch-main/functorch/experimental/__init__.py | # PyTorch forward-mode is not mature yet
from torch._functorch.eager_transforms import hessian, jacfwd, jvp
from torch._functorch.vmap import chunk_vmap
from torch._functorch.batch_norm_replacement import replace_all_batch_norm_modules_
from functorch import functionalize
| 273 | 44.666667 | 83 | py |
pytorch | pytorch-main/functorch/experimental/ops.py | from torch._ops import HigherOrderOperator # noqa: F401
| 57 | 28 | 56 | py |
pytorch | pytorch-main/functorch/notebooks/_src/plot_ensembling.py | """
==========================
Model ensembling
==========================
This example illustrates how to vectorize model ensembling using vmap.
What is model ensembling?
--------------------------------------------------------------------
Model ensembling combines the predictions from multiple models together.
Tradi... | 4,767 | 41.954955 | 89 | py |
pytorch | pytorch-main/functorch/notebooks/_src/plot_per_sample_gradients.py | """
==========================
Per-sample-gradients
==========================
What is it?
--------------------------------------------------------------------
Per-sample-gradient computation is computing the gradient for each and every
sample in a batch of data. It is a useful quantity in differential privacy
and opt... | 5,052 | 39.424 | 86 | py |
pytorch | pytorch-main/functorch/notebooks/_src/plot_jacobians_and_hessians.py | """
=============================
Jacobians, hessians, and more
=============================
Computing jacobians or hessians are useful in a number of non-traditional
deep learning models. It is difficult (or annoying) to compute these quantities
efficiently using a standard autodiff system like PyTorch Autograd; fun... | 7,950 | 44.434286 | 88 | py |
pytorch | pytorch-main/binaries/bench_gen/bench_gen.py | #!/usr/bin/env python3
import argparse
import ast
from caffe2.python.model_helper import ModelHelper
from caffe2.python.predictor import mobile_exporter
from caffe2.python import workspace, brew
def parse_kwarg(kwarg_str):
key, value = kwarg_str.split('=')
try:
value = ast.literal_eval(value)
ex... | 3,438 | 36.791209 | 90 | py |
pytorch | pytorch-main/ios/TestApp/custom_build/custom_build.py | import torch
import torchvision
import yaml
model = torchvision.models.mobilenet_v2(pretrained=True)
model.eval()
example = torch.rand(1, 3, 224, 224)
traced_script_module = torch.jit.trace(model, example)
ops = torch.jit.export_opnames(traced_script_module)
with open('mobilenetv2.yaml', 'w') as output:
yaml.dump(... | 333 | 26.833333 | 56 | py |
pytorch | pytorch-main/ios/TestApp/benchmark/trace_model.py | import torch
import torchvision
from torch.utils.mobile_optimizer import optimize_for_mobile
model = torchvision.models.mobilenet_v2(pretrained=True)
model.eval()
example = torch.rand(1, 3, 224, 224)
traced_script_module = torch.jit.trace(model, example)
optimized_scripted_module = optimize_for_mobile(traced_script_mo... | 508 | 41.416667 | 117 | py |
pytorch | pytorch-main/ios/TestApp/benchmark/coreml_backend.py | import torch
import torchvision
from torch.backends._coreml.preprocess import (
CompileSpec,
TensorSpec,
CoreMLComputeUnit,
)
def mobilenetv2_spec():
return {
"forward": CompileSpec(
inputs=(
TensorSpec(
shape=[1, 3, 224, 224],
),... | 1,000 | 22.833333 | 69 | py |
pytorch | pytorch-main/torchgen/gen_lazy_tensor.py | import argparse
import os
import pathlib
import re
from collections import Counter, namedtuple
from typing import (
Any,
Callable,
Dict,
Iterable,
Iterator,
List,
Optional,
Sequence,
Tuple,
Type,
Union,
)
import yaml
import torchgen.dest as dest
from torchgen.api.lazy impo... | 23,240 | 37.351485 | 118 | py |
pytorch | pytorch-main/torchgen/gen_functionalization_type.py | from dataclasses import dataclass
from typing import Callable, List, Optional, Tuple, Union
from torchgen.api import cpp, dispatcher
from torchgen.api.translate import translate
from torchgen.api.types import (
BaseCType,
Binding,
CType,
DispatcherSignature,
FunctionalizationLambda,
iTensorList... | 34,259 | 42.587786 | 129 | py |
pytorch | pytorch-main/torchgen/gen_backend_stubs.py | import argparse
import os
import pathlib
import re
from collections import Counter, defaultdict, namedtuple
from typing import Dict, List, Optional, Sequence, Set, Union
import yaml
import torchgen.api.dispatcher as dispatcher
import torchgen.dest as dest
from torchgen.api.types import DispatcherSignature
from torchg... | 22,374 | 35.680328 | 124 | py |
pytorch | pytorch-main/torchgen/context.py | import contextlib
import functools
from typing import Any, Callable, Dict, Iterator, List, Optional, Tuple, TypeVar, Union
import torchgen.local as local
from torchgen.model import (
BackendIndex,
DispatchKey,
NativeFunction,
NativeFunctionsGroup,
NativeFunctionsViewGroup,
)
from torchgen.utils im... | 3,974 | 29.813953 | 90 | py |
pytorch | pytorch-main/torchgen/native_function_generation.py | from collections import defaultdict
from typing import Dict, List, Optional, Sequence, Tuple, Union
import torchgen.api.dispatcher as dispatcher
from torchgen.api.translate import translate
from torchgen.api.types import Binding, DispatcherSignature, Expr
from torchgen.context import with_native_function
from torchge... | 29,113 | 44.993681 | 388 | py |
pytorch | pytorch-main/torchgen/utils.py | import contextlib
import functools
import hashlib
import os
import re
import sys
import textwrap
from argparse import Namespace
from dataclasses import fields, is_dataclass
from enum import auto, Enum
from typing import (
Any,
Callable,
Dict,
Generic,
Iterable,
Iterator,
List,
Literal,
... | 15,887 | 30.903614 | 110 | py |
pytorch | pytorch-main/torchgen/model.py | import dataclasses
import itertools
import re
from dataclasses import dataclass
from enum import auto, Enum
from typing import Callable, Dict, Iterator, List, Optional, Sequence, Set, Tuple, Union
from torchgen.utils import assert_never, NamespaceHelper, OrderedSet
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~... | 109,621 | 39.037253 | 438 | py |
pytorch | pytorch-main/torchgen/gen.py | import argparse
import functools
import json
import os
import pathlib
from collections import defaultdict, namedtuple, OrderedDict
from dataclasses import dataclass
from typing import (
Any,
Callable,
Dict,
List,
Literal,
Optional,
Sequence,
Set,
Tuple,
TypeVar,
Union,
)
imp... | 108,268 | 36.69812 | 130 | py |
pytorch | pytorch-main/torchgen/__init__.py | """torchgen
This module contains codegeneration utilities for PyTorch. It is used to
build PyTorch from source, but may also be used for out-of-tree projects
that extend PyTorch.
Note well that we provide no BC guarantees for torchgen. If you're interested
in using torchgen and want the PyTorch team to be aware, plea... | 348 | 30.727273 | 77 | py |
pytorch | pytorch-main/torchgen/gen_vmap_plumbing.py | import textwrap
from dataclasses import dataclass
from typing import List, Optional, Sequence, Tuple
from torchgen.api.translate import translate
from torchgen.api.types import DispatcherSignature
from torchgen.context import method_with_native_function
from torchgen.model import (
Argument,
BaseTy,
BaseTy... | 9,188 | 33.545113 | 119 | py |
pytorch | pytorch-main/torchgen/gen_executorch.py | import argparse
import os
import pathlib
from collections import defaultdict
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Sequence, TextIO, Tuple, Union
import yaml
# Parse native_functions.yaml into a sequence of NativeFunctions and Backend Indices.
from torchgen import d... | 33,659 | 35.31068 | 121 | py |
pytorch | pytorch-main/torchgen/executorch/model.py | # Represents all kernels used by an Executorch model.
# It maintains a Dict[OperatorName, Dict[ETKernelKey, BackendMetadata]] structure.
import itertools
from collections import defaultdict, namedtuple
from dataclasses import dataclass
from enum import IntEnum
from typing import Dict, List, Tuple, Union
from torchgen... | 7,710 | 33.891403 | 119 | py |
pytorch | pytorch-main/torchgen/executorch/parse.py | from collections import defaultdict, namedtuple
from typing import Any, Dict, List, Optional, Set, Tuple
import yaml
from torchgen.executorch.model import ETKernelIndex, ETKernelKey
from torchgen.gen import LineLoader, parse_native_yaml
from torchgen.model import (
BackendMetadata,
DispatchKey,
FunctionS... | 5,423 | 34.684211 | 107 | py |
pytorch | pytorch-main/torchgen/executorch/api/custom_ops.py | from collections import defaultdict
from dataclasses import dataclass
from typing import Dict, List, Optional, Sequence, Tuple
from torchgen import dest
# disable import sorting to avoid circular dependency.
from torchgen.api.types import DispatcherSignature # isort:skip
from torchgen.context import method_with_nat... | 4,846 | 35.719697 | 113 | py |
pytorch | pytorch-main/torchgen/executorch/api/et_cpp.py | from typing import List, Optional, Sequence, Set, Union
from torchgen import local
from torchgen.api.types import (
ArgName,
ArrayCType,
BaseCType,
Binding,
ConstRefCType,
CType,
MutRefCType,
NamedCType,
SpecialArgName,
TupleCType,
VectorCType,
voidT,
)
from torchgen.mod... | 12,960 | 34.124661 | 117 | py |
pytorch | pytorch-main/torchgen/executorch/api/unboxing.py | from dataclasses import dataclass
from typing import Callable, List, Sequence, Tuple
from torchgen.api.types import Binding, CType, NamedCType
from torchgen.model import (
Argument,
BaseTy,
BaseType,
ListType,
NativeFunction,
OptionalType,
Type,
)
connector = "\n\t"
# Return unboxing fun... | 7,764 | 35.285047 | 125 | py |
pytorch | pytorch-main/torchgen/executorch/api/types/types.py | from dataclasses import dataclass
from typing import Dict
from torchgen.api.types import (
BaseCppType,
BaseCType,
Binding,
boolT,
CType,
doubleT,
Expr,
longT,
MutRefCType,
NamedCType,
)
from torchgen.model import BaseTy
halfT = BaseCppType("torch::executor", "Half")
bfloat16T ... | 2,432 | 28.670732 | 93 | py |
pytorch | pytorch-main/torchgen/executorch/api/types/signatures.py | from dataclasses import dataclass
from typing import List, Optional, Set
import torchgen.api.cpp as aten_cpp
from torchgen.api.types import Binding, CType
from torchgen.model import FunctionSchema, NativeFunction
from .types import contextArg
@dataclass(frozen=True)
class ExecutorchCppSignature:
"""
This s... | 2,490 | 32.662162 | 87 | py |
pytorch | pytorch-main/torchgen/api/structured.py | from typing import List, Union
from torchgen.api import cpp
from torchgen.api.types import (
ArgName,
ArrayRefCType,
BaseCType,
Binding,
ConstRefCType,
dimnameListT,
intArrayRefT,
iOptTensorListRefT,
iTensorListRefT,
NamedCType,
OptionalCType,
optionalIntArrayRefT,
... | 6,166 | 37.786164 | 88 | py |
pytorch | pytorch-main/torchgen/api/autograd.py | import re
from dataclasses import dataclass
from typing import cast, Dict, List, Match, Optional, Sequence, Set, Tuple
from torchgen import local
from torchgen.api import cpp
from torchgen.api.types import BaseCType, Binding, NamedCType, tensorListT
from torchgen.model import (
FunctionSchema,
ListType,
N... | 34,665 | 43.67268 | 118 | py |
pytorch | pytorch-main/torchgen/api/python.py | from dataclasses import dataclass
from typing import Dict, List, Optional, Sequence, Set, Tuple, Union
from torchgen.api import cpp
from torchgen.api.types import Binding, CppSignature, CppSignatureGroup
from torchgen.gen import pythonify_default
from torchgen.model import (
Argument,
BaseTy,
BaseType,
... | 57,070 | 37.587559 | 150 | py |
pytorch | pytorch-main/torchgen/api/translate.py | from typing import Dict, List, NoReturn, Sequence, Union
from torchgen.api.types import (
ArrayRefCType,
BaseCType,
Binding,
boolT,
ConstRefCType,
deviceT,
Expr,
intArrayRefT,
iOptTensorListRefT,
layoutT,
ListCType,
longT,
memoryFormatT,
MutRefCType,
NamedCTy... | 19,140 | 43.410673 | 129 | py |
pytorch | pytorch-main/torchgen/api/dispatcher.py | import itertools
from typing import List, Sequence, Union
from torchgen.api import cpp
from torchgen.api.types import ArgName, Binding, CType, NamedCType
from torchgen.model import (
Argument,
FunctionSchema,
Return,
SelfArgument,
TensorOptionsArguments,
Type,
)
from torchgen.utils import asse... | 3,365 | 27.285714 | 88 | py |
pytorch | pytorch-main/torchgen/api/functionalization.py | from typing import List, Optional
from torchgen.api import dispatcher
from torchgen.api.types import (
BaseCType,
Binding,
boolT,
ConstRefCType,
CType,
longT,
NamedCType,
tensorT,
)
from torchgen.model import (
Argument,
BaseTy,
BaseType,
FunctionSchema,
NativeFuncti... | 6,931 | 38.163842 | 128 | py |
pytorch | pytorch-main/torchgen/api/unboxing.py | from typing import List, Tuple
from torchgen.api import cpp
from torchgen.api.types import Binding, CppSignatureGroup, CType
from torchgen.model import (
Argument,
BaseTy,
BaseType,
ListType,
NativeFunction,
OptionalType,
Type,
)
# This file generates the code for unboxing wrappers, i.e., ... | 9,474 | 37.052209 | 118 | py |
pytorch | pytorch-main/torchgen/api/meta.py | from torchgen.model import NativeFunctionsGroup
# Follows dispatcher calling convention, but:
# - Mutable arguments not allowed. Meta functions are always
# written in functional form. Look at FunctionSchema.signature()
# - No tensor returns; instead we return a TensorMeta describing
# the tensor in ques... | 482 | 36.153846 | 69 | py |
pytorch | pytorch-main/torchgen/api/native.py | from typing import List, Optional, Sequence, Union
from torchgen import local
from torchgen.api import cpp
from torchgen.api.types import (
ArgName,
BaseCType,
Binding,
boolT,
ConstRefCType,
CType,
deviceT,
layoutT,
ListCType,
MutRefCType,
NamedCType,
OptionalCType,
... | 5,136 | 32.357143 | 88 | py |
pytorch | pytorch-main/torchgen/api/lazy.py | from typing import Any, Dict, List, Optional, Tuple, Union
from torchgen.api.types import (
BaseCppType,
BaseCType,
boolT,
CType,
deviceT,
doubleT,
layoutT,
ListCType,
longT,
memoryFormatT,
NamedCType,
OptionalCType,
scalarT,
scalarTypeT,
stringT,
SymIntT... | 17,393 | 35.773784 | 109 | py |
pytorch | pytorch-main/torchgen/api/cpp.py | from typing import List, Optional, Sequence, Set, Union
from torchgen import local
from torchgen.api.types import (
ArgName,
ArrayCType,
ArrayRefCType,
BaseCType,
BaseTypeToCppMapping,
Binding,
boolT,
ConstRefCType,
CType,
dimnameListT,
intArrayRefT,
iTensorListRefT,
... | 16,286 | 34.101293 | 116 | py |
pytorch | pytorch-main/torchgen/api/ufunc.py | from dataclasses import dataclass
from typing import List, Optional
import torchgen.api.types as api_types
from torchgen.api import cpp, structured
from torchgen.api.types import (
ArgName,
BaseCppType,
BaseCType,
Binding,
ConstRefCType,
CType,
NamedCType,
scalarT,
)
from torchgen.mode... | 6,698 | 30.9 | 91 | py |
pytorch | pytorch-main/torchgen/api/types/types.py | """
Where should I add a new type? `types_base.py` vs `types.py`
This file defines data model classes for torchgen typing system, as well as some base types such as int32_t.
`types.py` defines ATen Tensor type and some c10 types, along with signatures that use these types.
The difference between these two files, is ... | 6,098 | 32.327869 | 114 | py |
pytorch | pytorch-main/torchgen/api/types/signatures.py | from dataclasses import dataclass
from typing import Iterator, List, Optional, Sequence, Set, Tuple, Union
from torchgen.model import (
BackendIndex,
FunctionSchema,
NativeFunction,
NativeFunctionsGroup,
NativeFunctionsViewGroup,
)
from .types_base import Binding, CType, Expr
@dataclass(frozen=... | 15,713 | 35.974118 | 124 | py |
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