repo stringlengths 2 99 | file stringlengths 13 225 | code stringlengths 0 18.3M | file_length int64 0 18.3M | avg_line_length float64 0 1.36M | max_line_length int64 0 4.26M | extension_type stringclasses 1
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|---|---|---|---|---|---|---|
DeepSpeed | DeepSpeed-master/tests/unit/inference/test_model_profiling.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import os
import time
import pytest
import torch
import deepspeed
from transformers import pipeline
from unit.common import DistributedTest
from deepspeed.accelerator import get_accelerator
@pytest.mark.inference
@pytest.m... | 1,813 | 31.981818 | 102 | py |
DeepSpeed | DeepSpeed-master/tests/unit/inference/test_inference.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import os
import time
import torch
import pytest
import itertools
import deepspeed
from deepspeed.git_version_info import torch_info
from unit.common import DistributedTest
from packaging import version as pkg_version
from d... | 20,794 | 34.668954 | 154 | py |
DeepSpeed | DeepSpeed-master/tests/unit/inference/test_checkpoint_sharding.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import os
import pytest
import torch
import deepspeed
from deepspeed.model_implementations import DeepSpeedTransformerInference
from unit.common import DistributedTest, DistributedFixture
from transformers import AutoConfig,... | 5,200 | 37.525926 | 117 | py |
DeepSpeed | DeepSpeed-master/tests/unit/pipe/test_pipe_module.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import copy
import torch
import torch.nn as nn
import deepspeed.comm as dist
import pytest
import deepspeed
from deepspeed.pipe import PipelineModule
from deepspeed.utils import RepeatingLoader
from deepspeed.accelerator ... | 3,377 | 30.277778 | 105 | py |
DeepSpeed | DeepSpeed-master/tests/unit/autotuning/test_autotuning.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import os
import pytest
from unit.simple_model import create_config_from_dict
from deepspeed.launcher import runner as dsrun
from deepspeed.autotuning.autotuner import Autotuner
from deepspeed.autotuning.scheduler import Res... | 3,248 | 40.126582 | 117 | py |
DeepSpeed | DeepSpeed-master/tests/unit/ops/sparse_attention/test_sparse_attention.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
# DeepSpeed note, some parts of code taken & adapted from commit c368a9fd1b2c9dee4cc94de9a6bb0be3d447be41
# https://github.com/ptillet/torch-blocksparse/blob/master/tests/test_softmax.py
# https://github.com/ptillet/torch-bl... | 9,912 | 38.337302 | 119 | py |
DeepSpeed | DeepSpeed-master/tests/unit/ops/aio/test_aio.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import pytest
import os
import filecmp
import torch
import deepspeed
import deepspeed.comm as dist
from deepspeed.accelerator import get_accelerator
from deepspeed.ops.op_builder import AsyncIOBuilder
from unit.common import... | 11,978 | 36.551724 | 115 | py |
DeepSpeed | DeepSpeed-master/tests/unit/ops/adam/test_cpu_adam.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import torch
import numpy as np
import pytest
from cpuinfo import get_cpu_info
import deepspeed
from deepspeed.accelerator import get_accelerator
from deepspeed.ops.adam import FusedAdam
from deepspeed.ops.op_builder import... | 4,900 | 37.289063 | 108 | py |
DeepSpeed | DeepSpeed-master/tests/unit/ops/adam/test_adamw.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import deepspeed
import torch
import pytest
from deepspeed.ops.adam import FusedAdam
from deepspeed.ops.adam import DeepSpeedCPUAdam
from unit.common import DistributedTest
from unit.simple_model import SimpleModel
# yapf:... | 3,044 | 38.545455 | 82 | py |
DeepSpeed | DeepSpeed-master/tests/unit/ops/quantizer/test_fake_quantization.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import torch
import pytest
from deepspeed.accelerator import get_accelerator
from deepspeed.ops import op_builder
quantizer_cuda_module = None
def allclose(x, y):
assert x.dtype == y.dtype
rtol, atol = {torch.floa... | 2,549 | 37.059701 | 102 | py |
DeepSpeed | DeepSpeed-master/tests/unit/ops/quantizer/test_quantize.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import pytest
import torch
from deepspeed.ops import op_builder
from deepspeed.accelerator import get_accelerator
inference_module = None
def run_quantize_ds(activations, num_groups, q_bits, is_symmetric_quant):
globa... | 5,713 | 36.84106 | 119 | py |
DeepSpeed | DeepSpeed-master/tests/unit/ops/adagrad/test_cpu_adagrad.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import torch
import numpy as np
import pytest
import deepspeed
from deepspeed.ops.adagrad import DeepSpeedCPUAdagrad
from deepspeed.accelerator import get_accelerator
from deepspeed.ops.op_builder import CPUAdagradBuilder
f... | 4,156 | 37.137615 | 116 | py |
DeepSpeed | DeepSpeed-master/tests/unit/ops/spatial/test_nhwc_bias_add.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import pytest
import torch
from deepspeed.ops.transformer.inference.bias_add import nhwc_bias_add
from deepspeed.accelerator import get_accelerator
def allclose(x, y):
assert x.dtype == y.dtype
rtol, atol = {torch.... | 3,671 | 41.697674 | 107 | py |
DeepSpeed | DeepSpeed-master/tests/unit/ops/accelerators/test_accelerator_backward.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import numpy as np
import torch
import pytest
import random
import copy
import os
from torch import nn
from deepspeed import DeepSpeedTransformerLayer, DeepSpeedTransformerConfig
from deepspeed.accelerator import get_acceler... | 10,934 | 37.914591 | 237 | py |
DeepSpeed | DeepSpeed-master/tests/unit/ops/accelerators/test_accelerator_forward.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import numpy as np
import torch
import pytest
import random
import copy
from torch import nn
from unit.modelingpreln import BertEncoder as BertEncoderPreln
from unit.modeling import BertLayerNorm, BertConfig, BertEncoder as ... | 12,953 | 40.652733 | 118 | py |
DeepSpeed | DeepSpeed-master/tests/unit/ops/transformer/inference/test_moe_res_matmult.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import pytest
import torch
import deepspeed
from deepspeed.accelerator import get_accelerator
from deepspeed.ops.op_builder import InferenceBuilder
from .inference_test_utils import allclose, get_dtypes
if not deepspeed.ops... | 1,885 | 37.489796 | 115 | py |
DeepSpeed | DeepSpeed-master/tests/unit/ops/transformer/inference/test_bias_geglu.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import pytest
import torch
import deepspeed
from deepspeed.ops.op_builder import InferenceBuilder
from deepspeed.accelerator import get_accelerator
from deepspeed.utils.types import ActivationFuncType
from .inference_test_ut... | 3,078 | 38.987013 | 114 | py |
DeepSpeed | DeepSpeed-master/tests/unit/ops/transformer/inference/test_layer_norm.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import deepspeed
import torch
import pytest
from deepspeed.accelerator import get_accelerator
from deepspeed.ops.op_builder import InferenceBuilder
from .inference_test_utils import allclose, get_dtypes
try:
import trito... | 8,934 | 43.232673 | 116 | py |
DeepSpeed | DeepSpeed-master/tests/unit/ops/transformer/inference/inference_test_utils.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import torch
from deepspeed.accelerator import get_accelerator
TOLERANCES = None
def get_tolerances():
global TOLERANCES
if TOLERANCES is None:
TOLERANCES = {torch.float32: (5e-4, 5e-5), torch.float16: (3e... | 1,062 | 24.309524 | 101 | py |
DeepSpeed | DeepSpeed-master/tests/unit/ops/transformer/inference/test_residual_add.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import pytest
import torch
import deepspeed
from deepspeed.accelerator import get_accelerator
from deepspeed.ops.op_builder import InferenceBuilder
from .inference_test_utils import get_dtypes
if not deepspeed.ops.__compati... | 5,157 | 41.983333 | 115 | py |
DeepSpeed | DeepSpeed-master/tests/unit/ops/transformer/inference/__init__.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
| 95 | 18.2 | 38 | py |
DeepSpeed | DeepSpeed-master/tests/unit/ops/transformer/inference/test_matmul.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import pytest
import torch
import deepspeed
from deepspeed.ops.op_builder import InferenceBuilder
if not deepspeed.ops.__compatible_ops__[InferenceBuilder.NAME]:
pytest.skip("Inference ops are not available on this syst... | 1,911 | 30.866667 | 90 | py |
DeepSpeed | DeepSpeed-master/tests/unit/ops/transformer/inference/test_bias_add.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import pytest
import torch
import deepspeed
from deepspeed.accelerator import get_accelerator
from deepspeed.ops.op_builder import InferenceBuilder
from .inference_test_utils import allclose, get_dtypes
if not deepspeed.ops... | 1,863 | 34.169811 | 114 | py |
DeepSpeed | DeepSpeed-master/tests/unit/ops/transformer/inference/test_bias_gelu.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import pytest
import torch
import deepspeed
from deepspeed.accelerator import get_accelerator
from deepspeed.ops.op_builder import InferenceBuilder
from .inference_test_utils import allclose, get_dtypes
from packaging import... | 2,213 | 37.842105 | 114 | py |
DeepSpeed | DeepSpeed-master/tests/unit/ops/transformer/inference/test_rms_norm.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import deepspeed
import torch
import pytest
from deepspeed.accelerator import get_accelerator
from deepspeed.ops.op_builder import InferenceBuilder # type: ignore
from .inference_test_utils import allclose, get_dtypes
if n... | 3,190 | 34.455556 | 90 | py |
DeepSpeed | DeepSpeed-master/tests/unit/ops/transformer/inference/test_attention.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import pytest
import torch
import deepspeed
# reference timplementation
def ref_torch_attention(q, k, v, mask, sm_scale):
p = torch.matmul(q, k.transpose(2, 3)) * sm_scale
p = torch.softmax(p.float() + mask, dim=-1... | 3,055 | 40.297297 | 113 | py |
DeepSpeed | DeepSpeed-master/tests/unit/ops/transformer/inference/test_bias_relu.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import pytest
import torch
import deepspeed
from deepspeed.accelerator import get_accelerator
from deepspeed.ops.op_builder import InferenceBuilder
from .inference_test_utils import allclose, get_dtypes
if not deepspeed.ops... | 1,932 | 36.173077 | 114 | py |
DeepSpeed | DeepSpeed-master/tests/unit/ops/transformer/inference/test_gelu.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import pytest
import torch
import deepspeed
from deepspeed.ops.op_builder import InferenceBuilder
if not deepspeed.ops.__compatible_ops__[InferenceBuilder.NAME]:
pytest.skip("Inference ops are not available on this syst... | 2,546 | 34.873239 | 97 | py |
DeepSpeed | DeepSpeed-master/tests/unit/ops/transformer/inference/test_softmax.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import pytest
import torch
import deepspeed
from deepspeed.ops.op_builder import InferenceBuilder
if not deepspeed.ops.__compatible_ops__[InferenceBuilder.NAME]:
pytest.skip("Inference ops are not available on this syst... | 1,716 | 32.019231 | 90 | py |
DeepSpeed | DeepSpeed-master/tests/perf/adam_test1.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import torch
from deepspeed.ops.adam import DeepSpeedCPUAdam
import time
from deepspeed.accelerator import get_accelerator
device = 'cpu'
model_size = 1 * 1024**3
param = torch.nn.Parameter(torch.ones(model_size, device=dev... | 808 | 28.962963 | 114 | py |
DeepSpeed | DeepSpeed-master/tests/perf/adam_test.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import torch
from deepspeed.ops.adam import DeepSpeedCPUAdam
import time
NUM_ITERS = 100
def _test_perf(param, optimizer_func):
optimizer = optimizer_func(param)
avg = 0
for i in range(NUM_ITERS):
for ... | 881 | 22.210526 | 88 | py |
DeepSpeed | DeepSpeed-master/tests/perf/adagrad_test.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import torch
from deepspeed.ops.adagrad import DeepSpeedCPUAdagrad
import time
NUM_ITERS = 100
def _test_perf(param, optimizer_func):
optimizer = optimizer_func(param)
avg = 0
for i in range(NUM_ITERS):
... | 893 | 22.526316 | 88 | py |
DeepSpeed | DeepSpeed-master/tests/small_model_debugging/test.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import torch
from deepspeed.pt.deepspeed_linear import LinearModuleForZeroStage3
from deepspeed.pt.log_utils import logger
from deepspeed.accelerator import get_accelerator
def see_memory_usage(message):
# Print messa... | 1,557 | 28.396226 | 106 | py |
DeepSpeed | DeepSpeed-master/tests/small_model_debugging/test_mics_config.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
"""
Testing on a 8 GPUs node
NDEV_PER_NODE=2 torchrun --nnodes 1 --nproc-per-node 8 test_mics_config.py
"""
import o... | 4,292 | 31.037313 | 110 | py |
DeepSpeed | DeepSpeed-master/tests/small_model_debugging/test_model.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import os
import json
import argparse
import torch
import deepspeed
from torch.utils.data.distributed import DistributedSampler
import deepspeed.comm as dist
class SimpleModel(torch.nn.Module):
def __init__(self, hidd... | 4,036 | 31.039683 | 118 | py |
DeepSpeed | DeepSpeed-master/tests/small_model_debugging/stage3_test.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import torch
import deepspeed
###################################
# Setup
###################################
class VerboseLinear(torch.nn.Linear):
def __init__(self, **kwargs):
print(f'Begin VerboseLinear._... | 2,394 | 25.318681 | 102 | py |
DeepSpeed | DeepSpeed-master/tests/onebit/test_nccl_backend.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import torch
import deepspeed.comm as dist
import numpy as np
import argparse
import deepspeed
import os
from deepspeed.runtime.comm.nccl import NcclBackend
from deepspeed.accelerator import get_accelerator
parser = argpar... | 3,515 | 36.404255 | 109 | py |
DeepSpeed | DeepSpeed-master/tests/onebit/test_mpi_backend.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
from mpi4py import MPI
import torch
import deepspeed.comm as dist
import numpy as np
import deepspeed
from deepspeed.runtime.comm.mpi import MpiBackend
from deepspeed.accelerator import get_accelerator
comm = MPI.COMM_WORL... | 3,412 | 37.348315 | 109 | py |
DeepSpeed | DeepSpeed-master/tests/onebit/test_nccl_perf.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import torch
import deepspeed.comm as dist
import numpy as np
import argparse
import deepspeed
import os
from deepspeed.runtime.comm.nccl import NcclBackend
from deepspeed.utils.timer import SynchronizedWallClockTimer
from ... | 3,065 | 30.285714 | 104 | py |
DeepSpeed | DeepSpeed-master/tests/onebit/test_mpi_perf.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
from mpi4py import MPI
import torch
import deepspeed
from deepspeed.runtime.comm.mpi import MpiBackend
# Configure wall clock timer
from deepspeed.utils.timer import SynchronizedWallClockTimer
from deepspeed.accelerator im... | 2,281 | 28.636364 | 87 | py |
DeepSpeed | DeepSpeed-master/tests/lightning/test_simple.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import torch
from pytorch_lightning import LightningModule, Trainer
from pytorch_lightning.strategies import DeepSpeedStrategy
from torch.utils.data import DataLoader, Dataset
class RandomDataset(Dataset):
def __init_... | 1,673 | 25.571429 | 109 | py |
DeepSpeed | DeepSpeed-master/tests/model/run_sanity_check.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
"""
Note: please copy webtext data to "Megatron-LM" folder, before running this script.
"""
import sys
import unittest
sys.path.append('../DeepSpeedExamples/Megatron_GPT2')
sys.path.append('../DeepSpeedExamples/BingBertSqua... | 1,298 | 27.23913 | 83 | py |
DeepSpeed | DeepSpeed-master/tests/model/Megatron_GPT2/test_common.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import unittest
import subprocess
import os
import time
class BaseTestCase(unittest.TestCase):
def __init__(self, methodName="DeepSpeed performance test"):
super(BaseTestCase, self).__init__(methodName)
... | 3,124 | 44.955882 | 122 | py |
DeepSpeed | DeepSpeed-master/tests/model/Megatron_GPT2/run_checkpoint_test.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
"""
Note: please copy webtext data to "Megatron-LM" folder, before running this script.
"""
import unittest
import subprocess
import os
import re
from .test_common import BaseTestCase
LAYERS = 2
HIDDEN_SIZE = 128
ATTN_HEADS... | 18,755 | 31.732984 | 120 | py |
DeepSpeed | DeepSpeed-master/tests/model/Megatron_GPT2/run_perf_baseline.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
"""
Note: please copy webtext data to "Megatron-LM" folder, before running this script.
"""
import unittest
import re
from test_common import BaseTestCase
class GPT2PerfBaselineTestCase(BaseTestCase):
def __init__(sel... | 3,524 | 25.908397 | 119 | py |
DeepSpeed | DeepSpeed-master/tests/model/Megatron_GPT2/run_perf_test.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
"""
Note: please copy webtext data to "Megatron-LM" folder, before running this script.
"""
import unittest
import re
from test_common import BaseTestCase
class GPT2PerfTestCase(BaseTestCase):
def __init__(self, metho... | 3,662 | 26.133333 | 119 | py |
DeepSpeed | DeepSpeed-master/tests/model/Megatron_GPT2/__init__.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
"""
Note: please copy webtext data to "Megatron-LM" folder, before running this script.
"""
from .run_func_test import GPT2FuncTestCase
from .run_checkpoint_test import GPT2CheckpointTestCase, checkpoint_suite
from .run_func... | 339 | 27.333333 | 83 | py |
DeepSpeed | DeepSpeed-master/tests/model/Megatron_GPT2/run_func_test.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
"""
Note: please copy webtext data to "Megatron-LM" folder, before running this script.
"""
import unittest
import os
import re
from .test_common import BaseTestCase
LAYERS = 2
HIDDEN_SIZE = 128
ATTN_HEADS = 8
SEQ_LEN = 64
... | 19,096 | 30.61755 | 113 | py |
DeepSpeed | DeepSpeed-master/tests/model/BingBertSquad/BingBertSquad_run_func_test.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
"""
Note: please copy webtext data to "Megatron-LM" folder, before running this script.
"""
import unittest
import os
import re
from .BingBertSquad_test_common import BaseTestCase
def grep_loss_from_file(file_name):
lo... | 5,243 | 28.460674 | 95 | py |
DeepSpeed | DeepSpeed-master/tests/model/BingBertSquad/BingBertSquad_test_common.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import unittest
import subprocess
import os
import time
class BaseTestCase(unittest.TestCase):
def __init__(self, methodName="DeepSpeed performance test"):
super(BaseTestCase, self).__init__(methodName)
... | 2,150 | 36.086207 | 116 | py |
DeepSpeed | DeepSpeed-master/tests/model/BingBertSquad/__init__.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
from .BingBertSquad_run_func_test import BingBertSquadFuncTestCase
from .BingBertSquad_run_func_test import suite
| 210 | 25.375 | 66 | py |
DeepSpeed | DeepSpeed-master/tests/model/BingBertSquad/test_e2e_squad.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import subprocess as sp
import os
from math import isclose
import sys
import pytest
import json
sys.path.append("../../../DeepSpeedExamples/BingBertSquad")
import evaluate as eval
squad_dir = "/data/BingBertSquad"
base_dir... | 3,710 | 28.452381 | 119 | py |
DeepSpeed | DeepSpeed-master/csrc/aio/py_test/ds_aio_handle.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
"""
Functionality of swapping optimizer tensors to/from (NVMe) storage devices.
"""
import torch
import os
import time
from multiprocessing import Pool, Barrier
from test_ds_aio_utils import report_results, task_log, task_ba... | 5,191 | 28.168539 | 109 | py |
DeepSpeed | DeepSpeed-master/csrc/aio/py_test/aio_bench_perf_sweep.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
"""
Functionality of swapping optimizer tensors to/from (NVMe) storage devices.
"""
import os
import sys
import argparse
import json
import itertools
import subprocess
import shutil
from test_ds_aio_utils import refine_integ... | 10,657 | 29.538682 | 118 | py |
DeepSpeed | DeepSpeed-master/csrc/aio/py_test/perf_sweep_utils.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
SCRIPT_PREFIX = '_aio_bench'
WRITE_OP_DESC = 'write'
READ_OP_DESC = 'read'
READ_IO_DIR = f'{SCRIPT_PREFIX}_{READ_OP_DESC}_io'
WRITE_IO_DIR = f'{SCRIPT_PREFIX}_{WRITE_OP_DESC}_io'
BENCH_LOG_DIR = f'{SCRIPT_PREFIX}_logs'
READ_... | 425 | 29.428571 | 55 | py |
DeepSpeed | DeepSpeed-master/csrc/aio/py_test/parse_aio_stats.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
"""
Functionality of swapping optimizer tensors to/from (NVMe) storage devices.
"""
import os
import argparse
READ_SPEED = 'read_speed'
WRITE_SPEED = 'write_speed'
PERF_METRICS = [READ_SPEED, WRITE_SPEED]
METRIC_SEARCH = ... | 3,835 | 24.744966 | 104 | py |
DeepSpeed | DeepSpeed-master/csrc/aio/py_test/aio_bench_generate_param.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
"""
Functionality of swapping optimizer tensors to/from (NVMe) storage devices.
"""
import os
import argparse
import json
from parse_aio_stats import READ_SPEED, WRITE_SPEED, get_sorted_results
from perf_sweep_utils import BE... | 2,814 | 29.268817 | 112 | py |
DeepSpeed | DeepSpeed-master/csrc/aio/py_test/test_ds_aio.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
"""
Functionality of swapping optimizer tensors to/from (NVMe) storage devices.
"""
import os
import argparse
import multiprocessing as mp
from ds_aio_basic import aio_basic_multiprocessing
from ds_aio_handle import aio_hand... | 2,738 | 30.848837 | 111 | py |
DeepSpeed | DeepSpeed-master/csrc/aio/py_test/validate_async_io.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
"""
Functionality of swapping optimizer tensors to/from (NVMe) storage devices.
"""
from deepspeed.ops.op_builder import AsyncIOBuilder
assert AsyncIOBuilder().is_compatible()
| 271 | 26.2 | 75 | py |
DeepSpeed | DeepSpeed-master/csrc/aio/py_test/ds_aio_basic.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
"""
Functionality of swapping optimizer tensors to/from (NVMe) storage devices.
"""
import torch
import os
import time
from multiprocessing import Pool, Barrier
from test_ds_aio_utils import report_results, task_log, task_ba... | 3,957 | 28.537313 | 109 | py |
DeepSpeed | DeepSpeed-master/csrc/aio/py_test/test_ds_aio_utils.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
"""
Functionality of swapping optimizer tensors to/from (NVMe) storage devices.
"""
BYTES_PER_GB = 1024**3
LOG_TIDS = [0]
def task_log(tid, msg):
if tid in LOG_TIDS:
print(f'tid {tid}: {msg}')
def task_barrie... | 1,790 | 29.355932 | 75 | py |
DeepSpeed | DeepSpeed-master/docs/code-docs/source/conf.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
# Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configurati... | 3,294 | 31.303922 | 79 | py |
DeepSpeed | DeepSpeed-master/release/bump_patch_version.py | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
from packaging import version as pkg_version
with open('../version.txt') as fd:
version = pkg_version.parse(fd.read())
with open('../version.txt', 'w') as fd:
fd.write(f'{version.major}.{version.minor}.{version.mic... | 408 | 26.266667 | 74 | py |
mBNN | mBNN-main/evaluate.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
import calibration as cal
from scipy.stats import norm
from thop import profile
def ll_mixture_normal(output, target, sigma):
exponent = -((target - output)**2).T/(2 * sigma**2)
log_coeff = -0.5*torch.log(2*torch.ten... | 7,111 | 38.731844 | 121 | py |
mBNN | mBNN-main/utils.py | import os
import pandas as pd
import numpy as np
import torch
import torchvision
import torchvision.transforms as transforms
from sklearn.preprocessing import MinMaxScaler
from sklearn.model_selection import train_test_split
from torch.utils.data import TensorDataset, DataLoader
def mkdir_p(path):
'''make dir if ... | 12,447 | 56.364055 | 199 | py |
mBNN | mBNN-main/MBNN/BSTS.py | import pandas as pd
import numpy as np
import argparse
import csv
from datetime import datetime
from torch import optim
from sklearn.linear_model import LinearRegression
from sklearn.preprocessing import MinMaxScaler, Normalizer
from Kalman_Filter import *
from MCMC import *
from Mask_Update import *
from models impor... | 6,742 | 37.752874 | 186 | py |
mBNN | mBNN-main/MBNN/image.py | import argparse
from datetime import date
import os
import numpy as np
import copy
from datetime import datetime
from progress.bar import ChargingBar as Bar
import pickle
import sys
sys.path.append('..')
from utils import *
from evaluate import *
from MBNN.models import *
from MBNN.MCMC import *
from MBNN.Mask_Updat... | 10,377 | 45.124444 | 393 | py |
mBNN | mBNN-main/MBNN/Polynomial.py | import argparse
from datetime import date
import os
import numpy as np
import copy
from datetime import datetime
from progress.bar import ChargingBar as Bar
import pickle
import seaborn as sns
import matplotlib.pyplot as plt
import sys
sys.path.append('..')
from utils import *
from evaluate import *
from MBNN.models... | 4,017 | 33.637931 | 135 | py |
mBNN | mBNN-main/MBNN/UCI.py | import argparse
from datetime import date
import os
import numpy as np
import copy
from datetime import datetime
from progress.bar import ChargingBar as Bar
import pickle
import sys
sys.path.append('..')
from utils import *
from evaluate import *
from MBNN.models import *
from MBNN.MCMC import *
from MBNN.Mask_Updat... | 9,295 | 43.908213 | 251 | py |
mBNN | mBNN-main/MBNN/Kalman_Filter.py | # Reference : https://github.com/ChadFulton/tsa-notebooks/blob/master/code_state_space.ipynb
import numpy as np
def kalman_filter(y, Z, H, T, Q, a_0, P_0):
# Dimensions
k_endog, nobs = y.shape
k_states = T.shape[0]
# Allocate memory for variabless
filtered_state = np.zeros((k_states, nobs))
f... | 2,681 | 32.949367 | 93 | py |
mBNN | mBNN-main/MBNN/models.py | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
class M_relu(nn.Module):
def __init__(self, input_dim, init_active_dim):
super().__init__()
self.input_dim = input_dim
self.init_active_dim = init_active_dim
self.active = nn.P... | 5,411 | 41.28125 | 134 | py |
mBNN | mBNN-main/MBNN/MCMC.py | import numpy as np
import torch
import copy
def ll_regression(output, target, sigma):
exponent = -((target - output)**2).sum() / (2 * sigma**2)
log_coeff = (-0.5*torch.log(2*torch.tensor(np.pi))-torch.log(sigma))*output.shape[0]
return (log_coeff + exponent)
def log_prior(model):
l_prior = torch... | 6,201 | 37.04908 | 110 | py |
mBNN | mBNN-main/MBNN/Mask_Update.py | import copy
import numpy as np
import torch
from itertools import permutations
from MCMC import *
def mask_update_dataloader(model, task, dataloader, datasize, lam=0.1, N_max=3, death_method="proposed", birth_method="random"):
model.zero_grad()
for n, p in model.named_parameters():
if 'active' in n:
... | 7,489 | 40.381215 | 205 | py |
LTL-GATA | LTL-GATA-main/src/main.py |
from argparse import ArgumentParser, Namespace
from copy import deepcopy
from gutils import init_logger
from args import add_args
from train import train
from test import test
import utils
parser = ArgumentParser()
add_args(parser)
logger = None
def main(args: Namespace):
config = utils.load_config(args.conf... | 1,529 | 29.6 | 75 | py |
LTL-GATA | LTL-GATA-main/src/test.py | from argparse import Namespace
import logging
import csv
from utils import save_trajectories
from evaluate import run as evaluate
from env import get_game_env
from agent import Agent
logger = logging.getLogger()
def test(config: Namespace):
# np.random.seed(config.training.random_seed)
# make game enviro... | 2,595 | 37.746269 | 78 | py |
LTL-GATA | LTL-GATA-main/src/tree.py | class Tree:
def __init__(self,) -> None:
...
class TreeNode:
def __init__(self, value, parent=None, children=None, mask=None):
self.value = value
self.parent = parent
self.children = children if children else []
self.mask = mask if mask is not None else [1.0] * 81
... | 6,246 | 35.109827 | 75 | py |
LTL-GATA | LTL-GATA-main/src/evaluate.py | from collections import defaultdict
from argparse import Namespace
import datetime
import logging
import pdb
import numpy as np
from env.cooking import RecipeWrappedEnv
from utils import expand_trajectories
from components import AgentModes
from agent import Agent
logger = logging.getLogger()
def run(env: Recipe... | 5,867 | 42.466667 | 78 | py |
LTL-GATA | LTL-GATA-main/src/args.py | from argparse import ArgumentParser
from datetime import datetime
from gutils.components import LogLevel
def add_args(parser: ArgumentParser) -> None:
parser.add_argument('--config', help='Config file path',
default='config.yaml')
parser.add_argument(
'--logs', help="Set outp... | 1,103 | 39.888889 | 79 | py |
LTL-GATA | LTL-GATA-main/src/belief_graph.py | from typing import List, Tuple, Set, Union
import torch
from textworld.logic import Proposition
from utils import triplet_to_proposition, proposition_to_triplet
def exists_triplet(triplets, arg1, arg2, relation):
for i, t in enumerate(triplets):
if arg1 in [t[0], "*"] and\
arg2 in [t[1], "*"... | 5,241 | 33.261438 | 74 | py |
LTL-GATA | LTL-GATA-main/src/state.py | from __future__ import annotations
from typing import List, Tuple
from copy import deepcopy, copy
from belief_graph import BeliefGraph
from ltl import LTL
class State:
def __init__(self,
observation: str = None,
action: str = None,
ltl: LTL = None,
... | 3,916 | 31.915966 | 76 | py |
LTL-GATA | LTL-GATA-main/src/utils.py | from __future__ import annotations
from typing import List, Dict, Any, Union, Tuple, Deque
from pathlib import Path, PosixPath
from argparse import Namespace
import pickle
from logic import Variable, Proposition
import numpy as np
import torch
import yaml
MISSING_WORDS = set()
CONSTANT_NAMES = {"P": "player", "I":... | 11,080 | 34.289809 | 114 | py |
LTL-GATA | LTL-GATA-main/src/components.py | from __future__ import annotations
from typing import NamedTuple, List, Dict, Union
from dataclasses import dataclass
from enum import Enum
from copy import copy
import logging
import numpy as np
from state import State
Actions = List[str]
logger = logging.getLogger()
@dataclass
class ResultsCSVField:
time:... | 3,874 | 25.909722 | 75 | py |
LTL-GATA | LTL-GATA-main/src/agent.py | from typing import Tuple, List, Dict, Any
from argparse import Namespace
from pathlib import Path
import logging
import copy
import json
import pdb
import torch.nn.functional as F
import numpy as np
import torch
from textworld import EnvInfos
from experience_replay import PrioritizedExperienceReplay
from components... | 29,311 | 44.234568 | 80 | py |
LTL-GATA | LTL-GATA-main/src/segment_tree.py | from typing import Callable
import operator
class SegmentTree:
def __init__(self, capacity: int,
operation: Callable, neutral_element: int) -> None:
"""
Build a Segment Tree data structure.
https://en.wikipedia.org/wiki/Segment_tree
Can be used as regular array, ... | 5,601 | 36.099338 | 79 | py |
LTL-GATA | LTL-GATA-main/src/experience_replay.py | from typing import Optional, List, Tuple
import logging
import pdb
from gutils import FixedSizeList
import numpy as np
from segment_tree import MinSegmentTree, SumSegmentTree
from utils import LinearSchedule
from components import Sample
logger = logging.getLogger()
class PrioritizedExperienceReplay:
def __i... | 7,334 | 38.86413 | 80 | py |
LTL-GATA | LTL-GATA-main/src/graph_updater.py | from typing import Tuple, List, Dict, Any
from pathlib import Path
import copy
import torch.nn.functional as F
import numpy as np
import torch
from utils import to_pt, max_len, pad_sequences, to_np
from model.layers import (
CQAttention, PointerSoftmax,
DecoderBlock, EncoderBlock, Embedding,
masked_softm... | 29,695 | 44.268293 | 79 | py |
LTL-GATA | LTL-GATA-main/src/train.py | from argparse import ArgumentParser, Namespace
from pathlib import Path
from collections import defaultdict, deque
from copy import deepcopy
import datetime
import logging
import copy
import csv
import pdb
import numpy as np
import tqdm
import yaml
from logic import proposition_from_textworld_logic
from components... | 27,639 | 44.68595 | 81 | py |
LTL-GATA | LTL-GATA-main/src/logic.py | from typing import List
from copy import copy
import pdb
from textworld.logic import Variable as TWVar, Proposition as TWProp
CONSTANT_NAMES = {"P": "player", "I": "player",
"ingredient": None, "slot": None, "RECIPE": "cookbook"}
def get_variable_name(name: str) -> str:
return CONSTANT_NAMES... | 2,406 | 31.093333 | 74 | py |
LTL-GATA | LTL-GATA-main/src/optim/radam.py | import math
import torch
from torch.optim.optimizer import Optimizer, required
class RAdam(Optimizer):
def __init__(self, params, lr=1e-3, betas=(0.9, 0.999), eps=1e-8, weight_decay=0, degenerated_to_sgd=True):
if not 0.0 <= lr:
raise ValueError("Invalid learning rate: {}".format(lr))
... | 11,028 | 39.848148 | 111 | py |
LTL-GATA | LTL-GATA-main/src/optim/__init__.py | from typing import Dict, Any
import torch
from optim.radam import RAdam
def get_optimizer(net: torch.nn.Module,
config: Dict[str, Any]) -> torch.optim.Optimizer:
# exclude some parameters from optimizer
param_frozen_list = [] # should be changed into torch.nn.ParameterList()
param_act... | 1,588 | 35.953488 | 77 | py |
LTL-GATA | LTL-GATA-main/src/env/ltl.py | from typing import Tuple, List, Dict, Any
from gym.envs.registration import register
from gym import spaces
import numpy as np
import gym
from ltl import progression as ltl_progression
from ltl.samplers import get_ltl_sampler
class SimpleLTLEnv(gym.Env):
"""
Emulates the behaviour of
from textworl... | 8,431 | 33 | 167 | py |
LTL-GATA | LTL-GATA-main/src/env/cooking.py | from typing import Tuple, List, Dict, Any, Union
from copy import copy, deepcopy
from pathlib import PosixPath
import logging
import random
import glob
import pdb
import re
import os
from textworld.gym.envs.textworld_batch import TextworldBatchGymEnv as TWEnv
from textworld.logic import Proposition, Variable
from tex... | 14,145 | 38.960452 | 159 | py |
LTL-GATA | LTL-GATA-main/src/env/__init__.py | from env.cooking import get_cooking_game_env
def get_game_env(game: str, **kwargs):
assert game in {'cooking'}
if game == 'cooking':
return get_cooking_game_env(**kwargs)
| 189 | 22.75 | 45 | py |
LTL-GATA | LTL-GATA-main/src/ltl/__init__.py | '''
Win facts for a single game are as:
[[],
[(Proposition('in', (Variable('red potato', 'f'), Variable('I', 'I'))),)],
[],
[(Proposition('chopped', (Variable('red potato', 'f'),)),)],
[(Proposition('in', (Variable('meal', 'meal'), Variable('I', 'I'))),)],
[(Proposition('consumed', (Variable... | 10,141 | 35.351254 | 79 | py |
LTL-GATA | LTL-GATA-main/src/ltl/progression.py | """
This code allows to progress LTL formulas. It requires installing the SPOT
library:
- https://spot.lrde.epita.fr/install.html
To encode LTL formulas, we use tuples, e.g.,
(
'and',
('until','True', ('and', 'd', ('until','True','c'))),
('until','True', ('and', 'a', ('until','True',... | 8,526 | 29.453571 | 78 | py |
LTL-GATA | LTL-GATA-main/src/ltl/translator.py | import re
from logic import Proposition, Variable, proposition_from_textworld_logic
import pdb
prep_map = {
'fry': 'fried',
'roast': 'roasted',
'grill': 'grilled',
'chop': 'chopped',
'dice': 'diced',
'slice': 'sliced',
}
ingredients = {
'banana', 'pork chop', 'carrot', 'parsley',
'chi... | 6,265 | 41.053691 | 127 | py |
LTL-GATA | LTL-GATA-main/src/model/features.py | from typing import List, Tuple
from argparse import Namespace
import pdb
from torch.autograd import Variable
import torch
from model.layers import Embedding, EncoderBlock, SelfAttention
from utils import max_len, to_pt, pad_sequences
class SimpleMLP(torch.nn.Module):
def __init__(self,
word_e... | 13,426 | 41.090909 | 78 | py |
LTL-GATA | LTL-GATA-main/src/model/utils.py | import torch
import math
def get_timing_signal(length: int, channels: int,
min_timescale: float = 1.0,
max_timescale: float = 1.0e4) -> torch.Tensor:
position = torch.arange(length).type(torch.float32)
num_timescales = channels // 2
log_timescale_increment = (ma... | 1,224 | 34 | 79 | py |
LTL-GATA | LTL-GATA-main/src/model/layers.py | import torch.nn.functional as F
import numpy as np
import torch
import h5py
from model.utils import PosEncoder, TreePosEncoder
class H5EmbeddingManager(object):
def __init__(self, h5_path):
f = h5py.File(h5_path, 'r')
self.W = np.array(f['embedding'])
# print("embedding data type=%s, shap... | 27,037 | 38.761765 | 143 | py |
LTL-GATA | LTL-GATA-main/src/model/pretrained_lm.py | from pathlib import Path
from transformers import DistilBertModel, DistilBertTokenizer
PRETRAINED_LANGUAGE_MODEL = None
TOKENIZER = None
def get_model_tokenizer(model: str, checkpoint: Path = None):
global PRETRAINED_LANGUAGE_MODEL
global TOKENIZER
if PRETRAINED_LANGUAGE_MODEL is None:
if model ... | 784 | 31.708333 | 72 | py |
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