python_code stringlengths 0 679k | repo_name stringlengths 9 41 | file_path stringlengths 6 149 |
|---|---|---|
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
"""Megatron tokenizers."""
from abc import ABC
from abc import abstractmethod
from .bert_tokenization import FullTokenizer as FullBertTokenizer
from .gpt2_tokenization import GPT2Tokenizer
def build_tokenizer(args):
"""Initialize tokenizer."""
i... | Megatron-LM-master | megatron/tokenizer/tokenizer.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import os
import pathlib
import subprocess
from torch.utils import cpp_extension
# Setting this param to a list has a problem of generating different
# compilation commands (with diferent order of architectures) and
# leading to recompilation of fused ke... | Megatron-LM-master | megatron/fused_kernels/__init__.py |
Megatron-LM-master | megatron/fused_kernels/tests/__init__.py | |
import math
import torch
from torch.nn import LayerNorm
from megatron.model.enums import AttnMaskType
from megatron.model.fused_layer_norm import MixedFusedLayerNorm
from megatron.model.fused_softmax import FusedScaleMaskSoftmax
from megatron.model.utils import attention_mask_func
from megatron.fused_kernels import l... | Megatron-LM-master | megatron/fused_kernels/tests/test_fused_kernels.py |
import os
import torch
import sys
from megatron import get_args, print_rank_0, get_tokenizer
from megatron.core import mpu
from megatron.checkpointing import fix_query_key_value_ordering
from megatron.checkpointing import get_checkpoint_tracker_filename
from megatron.checkpointing import get_checkpoint_name
from megat... | Megatron-LM-master | megatron/model/biencoder_model.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""This code is copied fron NVIDIA apex:
https://github.com/NVIDIA/apex
with some changes. """
import numbers
import torch
from torch.nn.parameter import Parameter
from torch.nn import init
import importlib
from megatron.core.utils import make_v... | Megatron-LM-master | megatron/model/fused_layer_norm.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Multiple choice model."""
import torch
from megatron import get_args, print_rank_last
from megatron.model.enums import AttnMaskType
from megatron.model.bert_model import bert_extended_attention_mask, bert_position_ids
from megatron.model.language_mode... | Megatron-LM-master | megatron/model/multiple_choice.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
"""Transformer based language model."""
import torch
import torch.nn.functional as F
from megatron import get_args
from megatron.core import mpu, tensor_parallel
from megatron.core.enums import ModelType
from megatron.core.models.common.rotary_pos_embedd... | Megatron-LM-master | megatron/model/language_model.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import enum
class LayerType(enum.Enum):
encoder = 1
decoder = 2
retro_encoder = 3
retro_decoder = 4
retro_decoder_with_retriever = 5
class AttnType(enum.Enum):
self_attn = 1
cross_attn = 2
class AttnMaskType(enum.Enum):
... | Megatron-LM-master | megatron/model/enums.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import torch
import torch.nn as nn
from megatron.model.enums import AttnMaskType
class ScaledUpperTriangMaskedSoftmax(torch.autograd.Function):
"""
Fused operation which performs following three operations in sequence
1. Scale the tensor.
... | Megatron-LM-master | megatron/model/fused_softmax.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Classification model."""
import torch
from megatron import get_args, print_rank_last
from megatron.model.enums import AttnMaskType
from megatron.model.bert_model import bert_extended_attention_mask, bert_position_ids
from megatron.model.language_model... | Megatron-LM-master | megatron/model/classification.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
"""BERT model."""
import torch
from megatron import get_args
from megatron.core import tensor_parallel
from megatron.model.enums import AttnMaskType
from megatron.model.language_model import parallel_lm_logits
from megatron.model.language_model import ge... | Megatron-LM-master | megatron/model/bert_model.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
from .fused_layer_norm import MixedFusedLayerNorm as LayerNorm
from .rms_norm import RMSNorm
from .distributed import DistributedDataParallel
from .bert_model import BertModel
from .gpt_model import GPTModel
from .t5_model import T5Model
from .language_mo... | Megatron-LM-master | megatron/model/__init__.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import torch
###### BIAS GELU FUSION/ NO AUTOGRAD ################
# 1/sqrt(2*pi)-> 0.3989423
# 1/sqrt(2) -> 0.70710678
# sqrt(2/pi) -> 0.79788456
# this function is tanh approximation of gelu
# actual gelu is:
# x * 0.5 * (1.0 + torch.erf(x * 0.70710... | Megatron-LM-master | megatron/model/fused_bias_gelu.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import math
from abc import ABC, abstractmethod
from contextlib import contextmanager
from typing import Dict, List
import torch
from megatron.core import mpu
from .module import MegatronModule
class MemoryBuffer:
def __init__(self, numel: int, nu... | Megatron-LM-master | megatron/model/distributed.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""T5 model."""
import torch
from megatron import get_args
from megatron.core import tensor_parallel
from megatron.model.enums import AttnMaskType
from megatron.model.language_model import parallel_lm_logits, get_language_model
from megatron.model import... | Megatron-LM-master | megatron/model/t5_model.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
"""Utilities for models."""
import math
import torch
from megatron import get_args
from megatron.model import LayerNorm, RMSNorm
def init_method_normal(sigma):
"""Init method based on N(0, sigma)."""
def init_(tensor):
return torch.nn.i... | Megatron-LM-master | megatron/model/utils.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
"""Transformer."""
from contextlib import nullcontext
import math
import numpy as np
import torch
import torch.nn.functional as F
from typing import Optional
from megatron import get_timers, get_args, get_retro_args, core, get_num_microbatches
from .modul... | Megatron-LM-master | megatron/model/transformer.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
"""GPT-2 model."""
import torch
from megatron import get_args
from megatron.core import tensor_parallel
from .module import MegatronModule
from .enums import AttnMaskType
from .language_model import parallel_lm_logits
from .language_model import get_lan... | Megatron-LM-master | megatron/model/gpt_model.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Megatron Module"""
import torch
from torch.autograd import Variable
from torch.nn.parameter import Parameter
from megatron import get_args
from megatron.core import mpu, tensor_parallel
_FLOAT_TYPES = (torch.FloatTensor, torch.cuda.FloatTensor)
_HAL... | Megatron-LM-master | megatron/model/module.py |
import os
import torch
from megatron import get_args, print_rank_0
from megatron.checkpointing import get_checkpoint_tracker_filename, get_checkpoint_name
from megatron.model import BertModel
from .module import MegatronModule
from megatron.core import mpu
from megatron.model.enums import AttnMaskType
from megatron.mo... | Megatron-LM-master | megatron/model/realm_model.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import torch
from torch import nn
class RMSNorm(torch.nn.Module):
def __init__(self, dim: int, eps: float = 1e-6):
super().__init__()
self.eps = eps
self.weight = nn.Parameter(torch.ones(dim))
def _norm(self, x):
... | Megatron-LM-master | megatron/model/rms_norm.py |
# Copyright (c) 2021 Microsoft
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# --------------------------------------------------------
# Modified by Chunyuan Li (chunyl@microsoft.com)
# Swin Transformer
# ----------------------------------... | Megatron-LM-master | megatron/model/vision/esvit_swin_backbone.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Vision Transformer(VIT) model."""
import torch
from torch.nn.init import trunc_normal_
from megatron import get_args
from megatron.model.utils import get_linear_layer
from megatron.model.vision.vit_backbone import VitBackbone, VitMlpHead
from megatron.... | Megatron-LM-master | megatron/model/vision/classification.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
import math
import apex
import einops
import torch
import torch.nn.functional as F
from megatron import get_args, print_rank_0
fr... | Megatron-LM-master | megatron/model/vision/inpainting.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Vision Transformer(VIT) model."""
import math
import einops
import torch
import apex
import torch.nn.functional as F
from megatron import get_args
from megatron.model.transformer import ParallelTransformer
from megatron.model.utils import (
get_lin... | Megatron-LM-master | megatron/model/vision/vit_backbone.py |
import torch.nn.functional as F
import torch
from megatron import print_rank_0, get_args
from megatron.core import mpu
from megatron.data.vit_dataset import ClassificationTransform
from megatron.data.image_folder import ImageFolder
_FEATURE_BANK = None
def build_data_loader(dataset, drop_last=True, shuffle=False):
... | Megatron-LM-master | megatron/model/vision/knn_monitor.py |
import warnings
import torch
import torch.nn.functional as F
def resize(input,
size=None,
scale_factor=None,
mode='nearest',
align_corners=None,
warning=True):
if warning:
if size is not None and align_corners:
input_h, input_w = tuple(int... | Megatron-LM-master | megatron/model/vision/utils.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the Apache license found in the
# LICENSE file in the root directory of this source tree.
# copied from https://github.com/facebookresearch/dino/blob/main/main_dino.py
# reworked/refactored some parts to make it run in Megatron.
... | Megatron-LM-master | megatron/model/vision/dino.py |
# Copyright (c) 2023, NVIDIA Corporation. All rights reserved.
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from functools import partial
from torch.nn.init import trunc_normal_
from megatron.model.transformer import DropPath
from megatron.model import LayerNorm
class Mlp(nn.Module)... | Megatron-LM-master | megatron/model/vision/mit_backbone.py |
# Copyright (c) 2021 Microsoft
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# --------------------------------------------------------
# Swin Transformer
# --------------------------------------------------------
import torch
import torch... | Megatron-LM-master | megatron/model/vision/swin_backbone.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Blendable dataset."""
import hashlib
import os
import time
import numpy as np
import torch
from megatron import print_rank_0
from megatron.core import mpu
class BlendableDataset(torch.utils.data.Dataset):
def __init__(self, datasets, weights, ... | Megatron-LM-master | megatron/data/blendable_dataset.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""BERT Style dataset."""
import numpy as np
import torch
from megatron import (
get_args,
get_tokenizer,
mpu,
print_rank_0
)
from megatron.data.dataset_utils import (
get_samples_mapping,
get_a_and_b_segments,
truncate_segmen... | Megatron-LM-master | megatron/data/bert_dataset.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""GPT style dataset."""
import hashlib
import os
import time
import numpy as np
import torch
from megatron import print_rank_0
from megatron.core import mpu
from megatron.data.blendable_dataset import BlendableDataset
from megatron.data.dataset_utils i... | Megatron-LM-master | megatron/data/gpt_dataset.py |
import itertools
import os
import pickle
import shutil
import numpy as np
import torch
from megatron import get_args
from megatron.core import mpu
def detach(tensor):
return tensor.detach().cpu().numpy()
class OpenRetreivalDataStore(object):
"""
Serializable data structure for holding data for blocks ... | Megatron-LM-master | megatron/data/realm_index.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Dataloaders."""
import random
import torch
import numpy as np
from torch.utils.data import Dataset
from megatron import get_args
from megatron.core import mpu
def build_pretraining_data_loader(dataset, consumed_samples):
"""Buld dataloader given... | Megatron-LM-master | megatron/data/data_samplers.py |
from . import indexed_dataset
| Megatron-LM-master | megatron/data/__init__.py |
# coding=utf-8
# Copyright 2018 The Google AI Language Team Authors, and NVIDIA.
#
# 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 ... | Megatron-LM-master | megatron/data/dataset_utils.py |
# BSD 3-Clause License
#
# Copyright (c) Soumith Chintala 2016,
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# * Redistributions of source code must retain the above copyright notice, this
#... | Megatron-LM-master | megatron/data/image_folder.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""Wikipedia dataset from DPR code for ORQA."""
from abc import ABC
import csv
import numpy as np
import random
import torch
from torch.utils.data import Dataset
from megatron import print_rank_0, get_args, get_tokenizer
from megatron.core import tensor_... | Megatron-LM-master | megatron/data/orqa_wiki_dataset.py |
"""AutoAugment data augmentation policy for ImageNet.
-- Begin license text.
MIT License
Copyright (c) 2018 Philip Popien
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, in... | Megatron-LM-master | megatron/data/autoaugment.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
from PIL import Image, UnidentifiedImageError
import numpy as np
import io
import torch
try:
from torchvision.transforms import InterpolationMode
BICUBIC = InterpolationMode.BICUBIC
except ImportError:
BICUBIC = Image.BICUBIC
from torchvision... | Megatron-LM-master | megatron/data/multimodal_dataset.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import os
import random
import numpy as np
import torch
import torchvision.transforms as T
from torchvision import datasets
from megatron import get_args
from megatron.data.image_folder import ImageFolder
from megatron.data.autoaugment import ImageNetPolicy... | Megatron-LM-master | megatron/data/vit_dataset.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""T5 Style dataset."""
import collections
import numpy as np
import torch
from megatron import get_tokenizer
from megatron.data.dataset_utils import (
create_masked_lm_predictions,
get_samples_mapping
)
class T5Dataset(torch.utils.data.Dataset... | Megatron-LM-master | megatron/data/t5_dataset.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# Essentially re-written in entirety
import os
import shutil
import struct
from enum import Enum
from functools import lru_cache
from itertoo... | Megatron-LM-master | megatron/data/indexed_dataset.py |
import os
import time
import numpy as np
import torch
from megatron import print_rank_0
from megatron.core import mpu, tensor_parallel
from megatron.data.dataset_utils import create_masked_lm_predictions, pad_and_convert_to_numpy
from megatron import get_args, get_tokenizer, print_rank_0
def get_one_epoch_dataloade... | Megatron-LM-master | megatron/data/realm_dataset_utils.py |
import itertools
import random
import numpy as np
from torch.utils.data import Dataset
from megatron import get_tokenizer
from megatron import get_args
from megatron.data.dataset_utils import get_indexed_dataset_
from megatron.data.realm_dataset_utils import get_block_samples_mapping
def make_attention_mask(source_b... | Megatron-LM-master | megatron/data/ict_dataset.py |
import os
import time
import numpy as np
import torch
from megatron import get_args, get_tokenizer, print_rank_0
from megatron.core import mpu, tensor_parallel
from megatron.data.dataset_utils import create_masked_lm_predictions, \
pad_and_convert_to_numpy
from megatron.dat... | Megatron-LM-master | megatron/data/biencoder_dataset_utils.py |
# This file isn't really a formal automated test, it's just a place to
# put some code used during development and manual testing of
# indexed_dataset.
from megatron.data import indexed_dataset
from megatron.tokenizer import build_tokenizer
import argparse
import os
import sys
import torch
script_dir = os.path.dirna... | Megatron-LM-master | megatron/data/test/test_indexed_dataset.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
"""For backward compatibility, we need the class definitions to deserialize."""
class LossScaler:
def __init__(self, scale=1):
self.cur_scale = scale
class DynamicLossScaler:
def __init__(self,
init_scale=2**32,
... | Megatron-LM-master | megatron/fp16_deprecated/loss_scaler.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
import atexit
import copy
import io
import os
import re
import subprocess
import tempfile
from distutils.version import LooseVersion
from setuptools import setup, find_packages, Extension
from setuptools.command.build_ext import build_ext
__version__ = '0... | atex-release | setup.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# See LICENSE for license information.
from . import nv_norms
from . import structured_sparsity
| atex-release | atex/__init__.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import os
import copy
import argparse
import time
from statistics import mean
# os.environ['TF_CPP_MIN_LOG_LEVEL'] = "3"
import numpy as np
import tensorflow as tf
from tensorflow.python.compiler.tensorrt import trt_convert as trt
SAVEDMODEL_PATH = "... | atex-release | atex/structured_sparsity/tftrt_infer.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# See LICENSE for license information.
from . import tf_asp
| atex-release | atex/structured_sparsity/__init__.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import inspect
import numpy as np
import os
import tempfile
import tensorflow as tf
from atex.structured_sparsity import tf_asp
import shutil
from tensorflow.keras import layers, optimizers
from tensorflow.python.platform import test
def GetSingleLayer... | atex-release | atex/structured_sparsity/tf_asp_optimizer_test.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
# WARNING:tensorflow:[TF-ASP] Allowlist is used: (Dense, Conv2D, )
# WARNING:tensorflow:[TF-ASP] Pruning list accepts the "kernel" variable from layer: dense_2 (type=Dense, shape=(128, 8))
# WARNING:tensorflow:[TF-ASP] Pruning list accepts the "kernel" va... | atex-release | atex/structured_sparsity/main.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import tensorflow as tf
import numpy as np
from tensorflow.keras import layers, optimizers
from tensorflow.python.platform import tf_logging
from itertools import permutations
# A PoC optimizer wrapper to perform pruning with masks.
class AspOptimizerWra... | atex-release | atex/structured_sparsity/tf_asp/tf_asp_optimizer.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import os
import numpy as np
import time
import ctypes
import subprocess
### support for searching on the GPU
gpus_tested = False
gpus_found = 0
E = None
def set_cpu_device():
global gpus_tested, gpus_found
gpus_tested = True
gpus_found = 0
def ... | atex-release | atex/structured_sparsity/tf_asp/permuting_search_utils.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
from .tf_asp_optimizer import AspOptimizerWrapper
from .tf_asp_optimizer_v2 import AspOptimizerWrapperV2
from .tf_asp_optimizer_v2 import check_pruned_layers
from .tf_asp_logging import *
| atex-release | atex/structured_sparsity/tf_asp/__init__.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import tensorflow as tf
SHOW_PRUNING_INFO = tf.compat.v1.logging.WARN # 30
SHOW_PERMUTATION_INFO = 29
SHOW_PERMUTATION_MORE_INFO = 28
SHOW_PERMUTATION_DEBUG_INFO = tf.compat.v1.logging.DEBUG
| atex-release | atex/structured_sparsity/tf_asp/tf_asp_logging.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import json
import numpy as np
import os
import pprint
import shutil
import tempfile
import tensorflow as tf
import time
from google.protobuf import json_format
from itertools import count
from tensorflow.keras import layers, optimizers, models
from tenso... | atex-release | atex/structured_sparsity/tf_asp/permuting_utils.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import numpy as np
import tensorflow as tf
from itertools import permutations
from tensorflow.keras import layers, optimizers
from tensorflow.python.platform import tf_logging
from .permuting_utils import permute_model
from .pruning_utils import get_2to... | atex-release | atex/structured_sparsity/tf_asp/tf_asp_optimizer_v2.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import tensorflow as tf
import numpy as np
from tensorflow.keras import layers, optimizers
from tensorflow.python.platform import tf_logging
def _m4n2_1d(matrix, patterns):
m, n = 4, 2
mat = tf.math.abs(tf.reshape(matrix, shape=(-1, m)))
pmax = tf... | atex-release | atex/structured_sparsity/tf_asp/pruning_utils.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
from .permuting_search_utils import *
################################################################################################################
# Exhaustive
# Try them all
# - order of columns within a group doesn't matter
# - order of group... | atex-release | atex/structured_sparsity/tf_asp/permuting_search.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
# ==============================================================================
from __future__ import absolute_import
from atex.nv_norms.python.ops.nv_norm_ops import fused_layer_norm_op
from atex.nv_norms.python.ops.nv_norm_ops import fused_layer_norm_... | atex-release | atex/nv_norms/__init__.py |
atex-release | atex/nv_norms/python/__init__.py | |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
# ==============================================================================
"""Use fused layer and instance norm ops in python."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os... | atex-release | atex/nv_norms/python/ops/nv_norm_ops.py |
atex-release | atex/nv_norms/python/ops/__init__.py | |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
# ==============================================================================
"""Tests for fused instance norm ops."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import itertools
import ... | atex-release | atex/nv_norms/tests/fused_instance_norm_test.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
# ==============================================================================
"""Tests for fused layer norm ops."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import itertools
import num... | atex-release | atex/nv_norms/tests/fused_layer_norm_test.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
# ==============================================================================
import argparse
from atex import nv_norms
import tensorflow as tf
import tensorflow_addons as tfa
from tensorflow.keras import layers, models
parser = argparse.ArgumentParser... | atex-release | atex/nv_norms/examples/sample_instanceN.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
# ==============================================================================
import argparse
from atex import nv_norms
import tensorflow as tf
from tensorflow.keras import layers, models
parser = argparse.ArgumentParser(description="Use --nvops to rep... | atex-release | atex/nv_norms/examples/sample_layerN.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
# ==============================================================================
import argparse
from atex import nv_norms
import tensorflow as tf
import time
from tensorflow.keras import mixed_precision
parser = argparse.ArgumentParser(description='Bench... | atex-release | atex/nv_norms/benchmarks/benchmark_layer_norm.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
# ==============================================================================
import argparse
from atex import nv_norms
import tensorflow as tf
import tensorflow_addons as tfa
import time
from tensorflow.keras import mixed_precision
parser = argparse.A... | atex-release | atex/nv_norms/benchmarks/benchmark_instance_norm.py |
"""
Copyright (C) 2018 NVIDIA Corporation. All rights reserved.
Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
"""
from __future__ import print_function
import torch
import numpy as np
from PIL import Image
from torch.autograd import Variable
import torchvisi... | FastPhotoStyle-master | process_stylization_ade20k_ssn.py |
"""
Copyright (C) 2018 NVIDIA Corporation. All rights reserved.
Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
"""
from __future__ import print_function
import time
import numpy as np
from PIL import Image
from torch.autograd import Variable
import torchvision... | FastPhotoStyle-master | process_stylization.py |
# Download code taken from Code taken from https://stackoverflow.com/questions/25010369/wget-curl-large-file-from-google-drive/39225039#39225039
import requests
def download_file_from_google_drive(id, destination):
URL = "https://docs.google.com/uc?export=download"
session = requests.Session()
response =... | FastPhotoStyle-master | download_models.py |
"""
Copyright (C) 2018 NVIDIA Corporation. All rights reserved.
Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
"""
import torch.nn as nn
class VGGEncoder(nn.Module):
def __init__(self, level):
super(VGGEncoder, self).__init__()
self.level... | FastPhotoStyle-master | models.py |
"""
Copyright (C) 2018 NVIDIA Corporation. All rights reserved.
Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
"""
src = '''
#include "/usr/local/cuda/include/math_functions.h"
#define TB 256
#define EPS 1e-7
__device__ bool InverseMat4x4(double m_in[4][4... | FastPhotoStyle-master | smooth_filter.py |
"""
Copyright (C) 2018 NVIDIA Corporation. All rights reserved.
Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
"""
from __future__ import division
import torch.nn as nn
import scipy.misc
import numpy as np
import scipy.sparse
import scipy.sparse.linalg
from ... | FastPhotoStyle-master | photo_smooth.py |
"""
Copyright (C) 2018 NVIDIA Corporation. All rights reserved.
Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
"""
from __future__ import print_function
import argparse
import os
import torch
import process_stylization_ade20k_ssn
from torch import nn
from phot... | FastPhotoStyle-master | demo_with_ade20k_ssn.py |
"""
Copyright (C) 2018 NVIDIA Corporation. All rights reserved.
Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
"""
from __future__ import print_function
import argparse
import os
import torch
from photo_wct import PhotoWCT
import process_stylization
parser = ... | FastPhotoStyle-master | process_stylization_folder.py |
import os
import torch
import torch.nn as nn
from torch.utils.serialization import load_lua
from models import VGGEncoder, VGGDecoder
from photo_wct import PhotoWCT
def weight_assign(lua, pth, maps):
for k, v in maps.items():
getattr(pth, k).weight = nn.Parameter(lua.get(v).weight.float())
getat... | FastPhotoStyle-master | converter.py |
"""
Copyright (C) 2018 NVIDIA Corporation. All rights reserved.
Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
"""
import numpy as np
from PIL import Image
import torch
import torch.nn as nn
from models import VGGEncoder, VGGDecoder
class PhotoWCT(nn.Module... | FastPhotoStyle-master | photo_wct.py |
"""
Copyright (C) 2018 NVIDIA Corporation. All rights reserved.
Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
"""
from __future__ import division
from PIL import Image
from torch import nn
import numpy as np
import cv2
from cv2.ximgproc import guidedFilter
... | FastPhotoStyle-master | photo_gif.py |
"""
Copyright (C) 2018 NVIDIA Corporation. All rights reserved.
Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
"""
from __future__ import print_function
import argparse
import torch
import process_stylization
from photo_wct import PhotoWCT
parser = argparse.A... | FastPhotoStyle-master | demo.py |
# Copyright (c) 2020–2021, NVIDIA Corporation.
#
# 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 agre... | data-science-blueprints-main | churn/generate.py |
#!/usr/bin/env python
# coding: utf-8
import os
default_spark_master = "local[*]"
app_name = "data-summary"
default_input_file = "churn-etl"
default_output_prefix = ""
default_input_kind = "parquet"
import argparse
import pyspark
import pyspark.sql.types as T
import pyspark.sql.functions as F
parser = parser = argp... | data-science-blueprints-main | churn/summarize.py |
#!/usr/bin/env python
# coding: utf-8
# Copyright (c) 2020–2021, NVIDIA Corporation.
#
# 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
#
# Un... | data-science-blueprints-main | churn/do-analytics.py |
#!/usr/bin/env python
# coding: utf-8
# Copyright (c) 2020–2021, NVIDIA Corporation.
#
# 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
#
# Un... | data-science-blueprints-main | churn/churn/etl.py |
# Copyright (c) 2020–2021, NVIDIA Corporation.
#
# 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 agre... | data-science-blueprints-main | churn/churn/augment.py |
# Copyright (c) 2020–2021, NVIDIA Corporation.
#
# 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 agre... | data-science-blueprints-main | churn/churn/eda.py |
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# 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 applic... | PixelView-master | setup.py |
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# 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 applic... | PixelView-master | PixelView/topLevel.py |
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# 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 applic... | PixelView-master | PixelView/__init__.py |
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# 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 applic... | PixelView-master | PixelView/cli.py |
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# 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 applic... | PixelView-master | PixelView/__main__.py |
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# 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 applic... | PixelView-master | PixelView/imageContainers/abstractImage.py |
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# 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 applic... | PixelView-master | PixelView/imageContainers/__init__.py |
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# 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 applic... | PixelView-master | PixelView/imageContainers/common.py |
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