python_code stringlengths 0 456k |
|---|
from doctr.file_utils import is_tf_available, is_torch_available
if is_tf_available():
from .tensorflow import *
elif is_torch_available():
from .pytorch import * # type: ignore[assignment]
|
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from copy import deepcopy
from typing import Any, Dict, List, Optional, Tuple, Union
import tensorflow as tf
from tensorflow.keras ... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from copy import deepcopy
from itertools import groupby
from typing import Any, Callable, Dict, List, Optional, Tuple
import torch
... |
from doctr.file_utils import is_tf_available, is_torch_available
if is_tf_available():
from .tensorflow import *
elif is_torch_available():
from .pytorch import * # type: ignore[assignment]
|
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from copy import deepcopy
from typing import Any, Dict, List, Optional, Tuple
import tensorflow as tf
from tensorflow.keras import ... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from copy import deepcopy
from typing import Any, Callable, Dict, List, Optional, Tuple
import torch
from torch import nn
from torc... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from typing import List, Tuple
import numpy as np
from ....datasets import encode_sequences
from ..core import RecognitionPostProc... |
from doctr.file_utils import is_tf_available, is_torch_available
if is_tf_available():
from .tensorflow import *
elif is_torch_available():
from .pytorch import * # type: ignore[assignment]
|
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from copy import deepcopy
from typing import Any, Dict, List, Optional, Tuple
import tensorflow as tf
from tensorflow.keras import ... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from copy import deepcopy
from typing import Any, Callable, Dict, List, Optional, Tuple
import torch
from torch import nn
from torc... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from typing import List, Tuple
import numpy as np
from ....datasets import encode_sequences
from ..core import RecognitionPostProc... |
from doctr.file_utils import is_tf_available, is_torch_available
if is_tf_available():
from .tensorflow import *
elif is_torch_available():
from .pytorch import * # type: ignore[assignment]
|
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from copy import deepcopy
from typing import Any, Dict, List, Optional, Tuple
import tensorflow as tf
from tensorflow.keras import ... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from copy import deepcopy
from typing import Any, Callable, Dict, List, Optional, Tuple
import torch
from torch import nn
from torc... |
from doctr.file_utils import is_tf_available
if is_tf_available():
from .tensorflow import *
else:
from .pytorch import * # type: ignore[assignment]
|
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from typing import Any, List, Tuple, Union
import numpy as np
import tensorflow as tf
from doctr.models.preprocessor import PrePro... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from typing import Any, List, Sequence, Tuple, Union
import numpy as np
import torch
from torch import nn
from doctr.models.prepro... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from typing import List, Tuple, Union
import numpy as np
from ..utils import merge_multi_strings
__all__ = ["split_crops", "remap... |
from .transformer import *
from .vision_transformer import *
|
from doctr.file_utils import is_tf_available, is_torch_available
if is_tf_available():
from .tensorflow import *
elif is_torch_available():
from .pytorch import * # type: ignore[assignment]
|
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
import math
from typing import Any, Tuple
import tensorflow as tf
from tensorflow.keras import layers
from doctr.utils.repr import... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
import math
from typing import Tuple
import torch
from torch import nn
__all__ = ["PatchEmbedding"]
class PatchEmbedding(nn.Modu... |
from doctr.file_utils import is_tf_available, is_torch_available
if is_tf_available():
from .tensorflow import *
elif is_torch_available():
from .pytorch import * # type: ignore[assignment]
|
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
import math
from typing import Any, Callable, Optional, Tuple
import tensorflow as tf
from tensorflow.keras import layers
from doc... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
# This module 'transformer.py' is inspired by https://github.com/wenwenyu/MASTER-pytorch and Decoder is borrowed
import math
from t... |
from doctr.file_utils import is_tf_available
if is_tf_available():
from .tensorflow import *
else:
from .pytorch import * # type: ignore[assignment]
|
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from typing import Any, List, Union
import numpy as np
import tensorflow as tf
from doctr.io.elements import Document
from doctr.m... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from typing import Any, List, Union
import numpy as np
import torch
from torch import nn
from doctr.io.elements import Document
fr... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from typing import Any, List, Optional, Tuple
import numpy as np
from doctr.models.builder import DocumentBuilder
from doctr.utils... |
from doctr.file_utils import is_tf_available, is_torch_available
if is_tf_available():
from .tensorflow import *
elif is_torch_available():
from .pytorch import * # type: ignore[assignment]
|
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
import math
from typing import Any, List, Tuple, Union
import numpy as np
import tensorflow as tf
from doctr.transforms import Nor... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
import math
from typing import Any, List, Tuple, Union
import numpy as np
import torch
from torch import nn
from torchvision.transf... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from typing import Any, List
from doctr.file_utils import is_tf_available, is_torch_available
from .. import detection
from ..prep... |
from .differentiable_binarization import *
from .linknet import *
from .zoo import *
|
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from typing import List
import cv2
import numpy as np
from doctr.utils.repr import NestedObject
__all__ = ["DetectionPostProcesso... |
from doctr.file_utils import is_tf_available
if is_tf_available():
from .tensorflow import *
else:
from .pytorch import *
|
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
import tensorflow as tf
__all__ = ["erode", "dilate"]
def erode(x: tf.Tensor, kernel_size: int) -> tf.Tensor:
"""Performs ero... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from torch import Tensor
from torch.nn.functional import max_pool2d
__all__ = ["erode", "dilate"]
def erode(x: Tensor, kernel_siz... |
from doctr.file_utils import is_tf_available, is_torch_available
if is_tf_available():
from .tensorflow import *
elif is_torch_available():
from .pytorch import * # type: ignore[assignment]
|
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
# Credits: post-processing adapted from https://github.com/xuannianz/DifferentiableBinarization
from copy import deepcopy
from typi... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from typing import Any, Callable, Dict, List, Optional
import numpy as np
import torch
from torch import nn
from torch.nn import fu... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
# Credits: post-processing adapted from https://github.com/xuannianz/DifferentiableBinarization
from typing import Dict, List, Tupl... |
from doctr.file_utils import is_tf_available, is_torch_available
if is_tf_available():
from .tensorflow import *
elif is_torch_available():
from .pytorch import * # type: ignore[assignment]
|
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
# Credits: post-processing adapted from https://github.com/xuannianz/DifferentiableBinarization
from copy import deepcopy
from typi... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from typing import Any, Callable, Dict, List, Optional, Tuple
import numpy as np
import torch
from torch import nn
from torch.nn im... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
# Credits: post-processing adapted from https://github.com/xuannianz/DifferentiableBinarization
from typing import Dict, List, Tupl... |
from doctr.file_utils import is_tf_available
if is_tf_available():
from .tensorflow import *
else:
from .pytorch import * # type: ignore[assignment]
|
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from typing import Any, Dict, List, Union
import numpy as np
import tensorflow as tf
from tensorflow import keras
from doctr.model... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from typing import Any, List, Union
import numpy as np
import torch
from torch import nn
from doctr.models.preprocessor import Pre... |
from .hub import *
|
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
# Inspired by: https://github.com/rwightman/pytorch-image-models/blob/master/timm/models/hub.py
import json
import logging
import o... |
from .faster_rcnn import *
|
from doctr.file_utils import is_tf_available, is_torch_available
if not is_tf_available() and is_torch_available():
from .pytorch import *
|
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from typing import Any, Dict
from torchvision.models.detection import FasterRCNN, faster_rcnn
from ...utils import load_pretrained... |
from .modules import *
|
from doctr.file_utils import is_tf_available, is_torch_available
from .base import *
if is_tf_available():
from .tensorflow import *
elif is_torch_available():
from .pytorch import * # type: ignore[assignment]
|
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
import random
from typing import Any, Callable, Dict, Iterable, List, Optional, Tuple, Union
import numpy as np
import tensorflow a... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
import math
from typing import Any, Dict, Optional, Tuple, Union
import numpy as np
import torch
from PIL.Image import Image
from t... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
import math
import random
from typing import Any, Callable, Dict, List, Tuple
import numpy as np
from doctr.utils.repr import Nest... |
from doctr.file_utils import is_tf_available, is_torch_available
if is_tf_available():
from .tensorflow import *
elif is_torch_available():
from .pytorch import *
|
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
import math
from copy import deepcopy
from typing import Tuple
import numpy as np
import tensorflow as tf
import tensorflow_addons ... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from copy import deepcopy
from typing import Tuple
import numpy as np
import torch
from torchvision.transforms import functional as... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from typing import Tuple, Union
import cv2
import numpy as np
from doctr.utils.geometry import rotate_abs_geoms
__all__ = ["crop_... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
import os
os.environ["USE_TORCH"] = "1"
import argparse
import logging
import cv2
import matplotlib.pyplot as plt
import torch
... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
import os
from doctr.io.elements import KIEDocument
os.environ["TF_CPP_MIN_LOG_LEVEL"] = "2"
import numpy as np
from tqdm import ... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
"""
Based on https://github.com/pytorch/pytorch/blob/master/torch/utils/collect_env.py
This script outputs relevant system environme... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
import argparse
import json
import os
from pathlib import Path
from tqdm import tqdm
os.environ["TF_CPP_MIN_LOG_LEVEL"] = "2"
fro... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
import os
os.environ["TF_CPP_MIN_LOG_LEVEL"] = "2"
import numpy as np
from tqdm import tqdm
from doctr import datasets
from doctr... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
import os
os.environ["TF_CPP_MIN_LOG_LEVEL"] = "2"
from doctr.file_utils import is_tf_available
from doctr.io import DocumentFile... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
"""
Borrowed & adapted from https://github.com/pytorch/vision/blob/main/.github/process_commit.py
This script finds the merger respo... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
import os
import doctr
PROJECT_NAME: str = "docTR API template"
PROJECT_DESCRIPTION: str = "Template API for Optical Character Rec... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
import tensorflow as tf
gpu_devices = tf.config.experimental.list_physical_devices("GPU")
if any(gpu_devices):
tf.config.experi... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from typing import Tuple
from pydantic import BaseModel, Field
# Recognition output
class RecognitionOut(BaseModel):
value: s... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
import time
from fastapi import FastAPI, Request
from fastapi.openapi.utils import get_openapi
from app import config as cfg
from ... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from fastapi import APIRouter, File, UploadFile, status
from app.schemas import RecognitionOut
from app.vision import reco_predicto... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from typing import List
from fastapi import APIRouter, File, UploadFile, status
from app.schemas import DetectionOut
from app.visi... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from typing import List
from fastapi import APIRouter, File, UploadFile, status
from app.schemas import OCROut
from app.vision imp... |
# Copyright (C) 2021-2023, Mindee.
# This program is licensed under the Apache License 2.0.
# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
from typing import Dict, List
from fastapi import APIRouter, File, UploadFile, status
from app.schemas import OCROut
from app.visi... |
import pytest_asyncio
import requests
from httpx import AsyncClient
from app.main import app
@pytest_asyncio.fixture(scope="session")
def mock_recognition_image(tmpdir_factory):
url = "https://user-images.githubusercontent.com/76527547/117133599-c073fa00-ada4-11eb-831b-412de4d28341.jpeg"
return requests.get(... |
import pytest
@pytest.mark.asyncio
async def test_text_recognition(test_app_asyncio, mock_recognition_image):
response = await test_app_asyncio.post("/recognition", files={"file": mock_recognition_image})
assert response.status_code == 200
assert response.json() == {"value": "invite"}
|
import numpy as np
import pytest
from scipy.optimize import linear_sum_assignment
from doctr.utils.metrics import box_iou
@pytest.mark.asyncio
async def test_text_detection(test_app_asyncio, mock_detection_image):
response = await test_app_asyncio.post("/detection", files={"file": mock_detection_image})
asse... |
import numpy as np
import pytest
from scipy.optimize import linear_sum_assignment
from doctr.utils.metrics import box_iou
@pytest.mark.asyncio
async def test_perform_ocr(test_app_asyncio, mock_detection_image):
response = await test_app_asyncio.post("/ocr", files={"file": mock_detection_image})
assert respon... |
import numpy as np
import pytest
from scipy.optimize import linear_sum_assignment
from doctr.utils.metrics import box_iou
@pytest.mark.asyncio
async def test_perform_kie(test_app_asyncio, mock_detection_image):
response = await test_app_asyncio.post("/kie", files={"file": mock_detection_image})
assert respon... |
# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# --------------------------------------------------------------------------
from __future__ import absolute_import
from __future__ import division
from __future__ import print_functi... |
import unittest
import math
from tensorboard_plugin_torch_profiler.profiler.overall_parser import (
merge_ranges, subtract_ranges_lists, intersection_ranges_lists, get_ranges_sum
)
def check_ranges_equal(ranges1, ranges2):
if len(ranges1) != len(ranges2):
return False
for i in range(len(ranges1))... |
import json
import unittest
import tensorboard_plugin_torch_profiler.profiler.trace as trace
from tensorboard_plugin_torch_profiler.profiler.data import RunProfileData
SCHEMA_VERSION = 1
WORKER_NAME = "worker0"
def parse_json_trace(json_content):
trace_json = json.loads(json_content)
profile = RunProfileDat... |
import os
import torch
import torch.nn as nn
import torch.backends.cudnn as cudnn
import torch.optim
import torch.utils.data
import torchvision
import torchvision.transforms as T
import torchvision.models as models
from torch.autograd.profiler import profile
model = models.resnet50(pretrained=True)
model.cuda()
cudnn... |
import os
import torch
import torch.nn as nn
import torch.backends.cudnn as cudnn
import torch.optim
import torch.utils.data
import torchvision
import torchvision.transforms as T
import torchvision.datasets as datasets
import torchvision.models as models
import torch.profiler
model = models.resnet50(pretrained=True)
... |
# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# --------------------------------------------------------------------------
from __future__ import absolute_import
from __future__ import division
from __future__ import print_functi... |
# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# --------------------------------------------------------------------------
# Entry point for Pytorch TensorBoard plugin package.
|
# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# --------------------------------------------------------------------------
from __future__ import absolute_import
from __future__ import division
from __future__ import print_functi... |
# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# --------------------------------------------------------------------------
from __future__ import absolute_import
from __future__ import division
from __future__ import print_functi... |
# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# --------------------------------------------------------------------------
from __future__ import absolute_import
from __future__ import division
from __future__ import print_functi... |
# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# --------------------------------------------------------------------------
from __future__ import absolute_import
from __future__ import division
from __future__ import print_functi... |
# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# --------------------------------------------------------------------------
from .loader import RunLoader
__all__ = ["RunLoader"]
|
# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# --------------------------------------------------------------------------
from __future__ import absolute_import
from __future__ import division
from __future__ import print_functi... |
# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# --------------------------------------------------------------------------
from __future__ import absolute_import
from __future__ import division
from __future__ import print_functi... |
# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# --------------------------------------------------------------------------
import pandas as pd
class KernelParser:
def __init__(self):
self.kernel_stat = None
def... |
# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# --------------------------------------------------------------------------
import sys
from .. import utils
from .trace import EventTypes
logger = utils.get_logger()
def merge_ra... |
# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# --------------------------------------------------------------------------
from __future__ import absolute_import
from __future__ import division
from __future__ import print_functi... |
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