id int64 0 190k | prompt stringlengths 21 13.4M | docstring stringlengths 1 12k ⌀ |
|---|---|---|
23,226 | import os
import shutil
import json
import sys
import numpy as np
from .log import log_or_print
from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP
def print_mat(mat, name="tmp mat", col=20, t=0, channel=sys.stdout):
max_val = mat.max()
min_val = mat.min()
sum_val = mat.sum()
if isinstance(max_val, float) or ... | null |
23,227 | import os
import shutil
import json
import sys
import numpy as np
from .log import log_or_print
from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP
def latest_file(folder, file_checker=None):
lists = os.listdir(folder)
lists.sort(key=lambda fn: os.path.getmtime(os.path.join(folder, fn)))
for file_name in lists[... | null |
23,228 | import sys
import os
import logging
import io
from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP, NNDCT_DEBUG_LVL
GLOBAL_MAP = GlobalMap()
def nndct_info_print(string):
logger = GLOBAL_MAP.get_ele(NNDCT_KEYS.LOGGER)
if logger:
logger.info("[NNDCT_INFO] {}".format(string))
else:
print("[NNDCT_INFO] {}"... | null |
23,229 | import sys
import os
import logging
import io
from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP, NNDCT_DEBUG_LVL
GLOBAL_MAP = GlobalMap()
def nndct_warn_print(string):
if True == GLOBAL_MAP.get_ele(NNDCT_KEYS.WARN_FLAG):
logger = GLOBAL_MAP.get_ele(NNDCT_KEYS.LOGGER)
if logger:
logger.warning("[NND... | null |
23,230 | import sys
import os
import logging
import io
from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP, NNDCT_DEBUG_LVL
GLOBAL_MAP = GlobalMap()
def nndct_error_print(string):
if True == GLOBAL_MAP.get_ele(NNDCT_KEYS.ERROR_FLAG):
logger = GLOBAL_MAP.get_ele(NNDCT_KEYS.LOGGER)
if logger:
logger.error("[NND... | null |
23,231 | import sys
import os
import logging
import io
from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP, NNDCT_DEBUG_LVL
def obj_to_str(obj):
if isinstance(obj, list):
string = '\n'.join(["{}".format(n) for n in obj])
elif isinstance(obj, dict):
string = '\n'.join(["{} : {}".format(k, v) for k, v in obj.items()]... | null |
23,232 | import sys
import os
import logging
import io
from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP, NNDCT_DEBUG_LVL
GLOBAL_MAP = GlobalMap()
def nndct_info(func):
def wrapper(*args, **kwargs):
info_flag = GLOBAL_MAP.get_ele(NNDCT_KEYS.INFO_FLAG)
if info_flag == True:
print("[NNDCT_INFO]", end='')
... | null |
23,233 | import sys
import os
import logging
import io
from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP, NNDCT_DEBUG_LVL
GLOBAL_MAP = GlobalMap()
def nndct_warn(func):
def wrapper(*args, **kwargs):
warn_flag = GLOBAL_MAP.get_ele(NNDCT_KEYS.WARN_FLAG)
if warn_flag == True:
print("[NNDCT_WARN]", end='')
... | null |
23,234 | import sys
import os
import logging
import io
from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP, NNDCT_DEBUG_LVL
GLOBAL_MAP = GlobalMap()
def nndct_debug(func):
def wrapper(*args, **kwargs):
debug_flag = GLOBAL_MAP.get_ele(NNDCT_KEYS.DEBUG_FLAG)
if debug_flag == True:
print("[NNDCT_DEBUG]", end=''... | null |
23,235 | import sys
import os
import logging
import io
from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP, NNDCT_DEBUG_LVL
GLOBAL_MAP = GlobalMap()
def nndct_error(func):
def wrapper(*args, **kwargs):
error_flag = GLOBAL_MAP.get_ele(NNDCT_KEYS.ERROR_FLAG)
if error_flag == True:
print("[NNDCT_ERROR]", end=''... | null |
23,236 | import sys
import os
import logging
import io
from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP, NNDCT_DEBUG_LVL
import logging as _logging
from logging import DEBUG
from logging import ERROR
from logging import FATAL
from logging import INFO
from logging import WARN
from logging import NOTSET
def get_nndct_logger... | null |
23,237 | import sys
import os
import logging
import io
from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP, NNDCT_DEBUG_LVL
def get_config_str(obj,
title,
ignore_prefix=[],
ignore_suffix=[],
ignore_keys=[]):
assert hasattr(
obj, 'default_kwarg... | null |
23,238 | import math
from nndct_shared.base import NNDCT_OP
def calculate_op_scale(rec, node):
scale = 1.0
if node.op.type in [NNDCT_OP.MEAN]:
max_factor = math.ceil(math.log(rec * 128,2))
diff = 1.0
multi_factor = 0.0
shift_factor = 0.0
for shift_factor_ in range(max_factor):
factor = round((2 *... | null |
23,241 | from nndct_shared.utils.tensor_util import DataFormatMap
from typing import List
def generate_indices_group(indices: List[int], dim_size: int,
groups: int) -> List[List[int]]:
indices_set = set(indices)
interval: int = dim_size // groups
start_idx = 0
end_idx = interval
ret: List[L... | null |
23,242 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import abc
import copy
import json
import numpy as np
import os
from typing import List
from nndct_shared.base.key_names import FrameworkType
from nndct_shared.pruning import errors
from nndct_shared.pruning imp... | null |
23,243 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import abc
import copy
import json
import numpy as np
import os
from typing import List
from nndct_shared.base.key_names import FrameworkType
from nndct_shared.pruning import errors
from nndct_shared.pruning imp... | null |
23,247 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import logging as _logging
import os as _os
import sys as _sys
import time as _time
import traceback as _traceback
from logging import DEBUG
from logging import ERROR
from logging import FATAL
from logging impor... | null |
23,249 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import logging as _logging
import os as _os
import sys as _sys
import time as _time
import traceback as _traceback
from logging import DEBUG
from logging import ERROR
from logging import FATAL
from logging impor... | null |
23,250 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import logging as _logging
import os as _os
import sys as _sys
import time as _time
import traceback as _traceback
from logging import DEBUG
from logging import ERROR
from logging import FATAL
from logging impor... | null |
23,253 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import logging as _logging
import os as _os
import sys as _sys
import time as _time
import traceback as _traceback
from logging import DEBUG
from logging import ERROR
from logging import FATAL
from logging impor... | null |
23,255 | import collections
import json
import os
from nndct_shared.pruning.pruning_lib import PruningSpec, NodeGroup
from nndct_shared.pruning import errors
from nndct_shared.utils import io
from typing import List
class SubnetSearcher(object):
def __init__(self, groups: List[NodeGroup]):
self._groups = groups
self._... | null |
23,256 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from typing import List, Mapping, Any, Union, Tuple
import collections
from nndct_shared.base.key_names import NNDCT_OP as OpTypes
from nndct_shared.nndct_graph.base_node import Node
from nndct_shared.metaclass ... | null |
23,269 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from typing import List, Mapping, Any, Union, Tuple
import collections
from nndct_shared.base.key_names import NNDCT_OP as OpTypes
from nndct_shared.nndct_graph.base_node import Node
from nndct_shared.metaclass ... | null |
23,271 | from collections import deque
def graph_search_handler(start_node,
generator,
frontier,
handler=None,
gen_params={}):
frontier.append(start_node)
explored = set()
while frontier:
node = frontier.pop()
explo... | null |
23,276 | import sys
from typing import List, Optional
from nndct_shared.base import NNDCT_OP
from nndct_shared.nndct_graph import Graph, Operation, Node, Block
from nndct_shared.nndct_graph import operator_definition as base_op
from nndct_shared.utils import NndctOption, NndctScreenLogger
def convert_graph_to_block_node(top_gra... | null |
23,280 | import math
import itertools
from typing import List, Dict, Any, NoReturn, Tuple
import numpy as np
from functools import partial
from nndct_shared.base import NNDCT_OP, NNDCT_KEYS
from nndct_shared.nndct_graph import Tensor, Node
from .xgraph import XGraph
from nndct_shared.utils import calculate_op_scale, DataXopErro... | null |
23,285 | import math
import itertools
from typing import List, Dict, Any, NoReturn, Tuple
import numpy as np
from functools import partial
from nndct_shared.base import NNDCT_OP, NNDCT_KEYS
from nndct_shared.nndct_graph import Tensor, Node
from .xgraph import XGraph
from nndct_shared.utils import calculate_op_scale, DataXopErro... | null |
23,289 | import math
import itertools
from typing import List, Dict, Any, NoReturn, Tuple
import numpy as np
from functools import partial
from nndct_shared.base import NNDCT_OP, NNDCT_KEYS
from nndct_shared.nndct_graph import Tensor, Node
from .xgraph import XGraph
from nndct_shared.utils import calculate_op_scale, DataXopErro... | null |
23,300 | from collections import defaultdict
from nndct_shared.utils import NndctDebugLogger, NndctOption
def log_debug_info(msg):
if NndctOption.nndct_inspect_debug.value:
NndctDebugLogger.write(f"{msg}\n") | null |
23,301 | import copy
import networkx as nx
from networkx.algorithms import is_isomorphic
from nndct_shared.base import NNDCT_OP
from nndct_shared.inspector.utils import build_xir_nndct_op_map, log_debug_info
from nndct_shared.compile.xir_helper import XIRHelper
from .graph import Graph, Node
_SIMULATION_PATTERNS = [
{"name":... | null |
23,303 | import copy
import networkx as nx
from networkx.algorithms import is_isomorphic
from nndct_shared.base import NNDCT_OP
from nndct_shared.inspector.utils import build_xir_nndct_op_map, log_debug_info
from nndct_shared.compile.xir_helper import XIRHelper
from .graph import Graph, Node
def get_templates_from_dpu_compiler(... | null |
23,304 | import copy
import networkx as nx
from networkx.algorithms import is_isomorphic
from nndct_shared.base import NNDCT_OP
from nndct_shared.inspector.utils import build_xir_nndct_op_map, log_debug_info
from nndct_shared.compile.xir_helper import XIRHelper
from .graph import Graph, Node
class Graph(object):
def __ini... | null |
23,305 | from typing import Mapping
from nndct_shared.nndct_graph.base_graph import Graph
from nndct_shared.nndct_graph.base_node import Node
from nndct_shared.expanding.op_modifier import op_modifier
from nndct_shared.expanding.spec import DataInsert, GenericStructuredExpanding, StructuredExpanding
from nndct_shared.expanding.... | null |
23,306 | from typing import Mapping
from nndct_shared.expanding.spec import BatchNormStructuredExpanding, InstanceNormStructuredExpanding, \
DataInsert, GenericStructuredExpanding, StructuredExpanding, WeightedNodeStructuredExpanding
from nndct_shared.nndct_graph.base_graph import Graph
from nndct_shared.nndct_graph.base_node... | null |
23,312 | from typing import Mapping
from nndct_shared.expanding.spec import BatchNormStructuredExpanding, InstanceNormStructuredExpanding, \
DataInsert, GenericStructuredExpanding, StructuredExpanding, WeightedNodeStructuredExpanding
from nndct_shared.nndct_graph.base_graph import Graph
from nndct_shared.nndct_graph.base_node... | null |
23,314 | import numpy as np
import math
from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP
from nndct_shared.utils import NndctOption
from nndct_shared.algorithms import breadth_first_search_handler
from .quant_ops import normal_quant_neuron
def normal_quant_neuron(data,
maxamps=[[32768], [2048]],
... | null |
23,319 | import numpy as np
import math
from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP
from nndct_shared.utils import NndctOption
from nndct_shared.algorithms import breadth_first_search_handler
from .quant_ops import normal_quant_neuron
def maybe_get_quantizer(quantizer=None):
def quant_channel_scale_params(node, channe... | null |
23,328 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from nndct_shared.base.key_names import NNDCT_OP
from nndct_shared.base.key_names import FrameworkType
from nndct_shared.nndct_graph import base_tensor
class DataFormatMap(object):
"""A dict... | null |
23,333 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import logging as _logging
import os as _os
import sys as _sys
import time as _time
import traceback as _traceback
from logging import DEBUG
from logging import ERROR
from logging import FATAL
from logging impor... | null |
23,334 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import logging as _logging
import os as _os
import sys as _sys
import time as _time
import traceback as _traceback
from logging import DEBUG
from logging import ERROR
from logging import FATAL
from logging impor... | null |
23,336 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import logging as _logging
import os as _os
import sys as _sys
import time as _time
import traceback as _traceback
from logging import DEBUG
from logging import ERROR
from logging import FATAL
from logging impor... | null |
23,346 | import numpy as np
from nndct_shared.base import NNDCT_OP
def get_in_out_channel_idx(ndim, optype, data_formats):
def get_tensor_in_dim(tensor, optype, data_formats):
in_idx, _ = get_in_out_channel_idx(tensor.ndim, optype, data_formats)
return tensor.shape[in_idx] | null |
23,350 | from typing import TypeVar, NoReturn, Optional, Iterator, List
from .option_list import NndctOption
from .option_def import Option, T
class NndctOption(object):
nndct_help = Option(name="help", dtype=bool, default=False, action="store_true",
help="list all api usage description")
nndct_quan... | null |
23,360 | from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP, NNDCT_DEBUG_LVL
from .log import nndct_debug_print
def remove_trans_scp_prefix(name, scp=None):
name = remove_prefix(name, scp)
if name.startswith(NNDCT_KEYS.TRANS_SCOPE):
name = '/'.join(name.split('/')[1:])
return name
def scoped_untrans_name(name, scp)... | null |
23,361 | from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP, NNDCT_DEBUG_LVL
from .log import nndct_debug_print
def remove_prefix(obj, prefix):
if obj is None:
return obj
if prefix is None or prefix == '':
return obj
if isinstance(prefix, str):
if isinstance(obj, str) and len(prefix) > 0 and obj.startswith(p... | null |
23,362 | from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP, NNDCT_DEBUG_LVL
from .log import nndct_debug_print
def remove_trans_scp_prefix(name, scp=None):
name = remove_prefix(name, scp)
if name.startswith(NNDCT_KEYS.TRANS_SCOPE):
name = '/'.join(name.split('/')[1:])
return name
GLOBAL_MAP = GlobalMap()
def nndc... | null |
23,366 | from enum import Enum
def readable_num(number):
s = ''
if number < 0:
s += '-'
number = -number
if number < 1000:
s += '%d' % number
elif number > 1e15:
s += '%0.3G' % number
else:
units = 'KMGT'
unit_index = 0
while number > 1000000:
number /= 1000
unit_index += 1
... | null |
23,367 | from enum import Enum
def print_table(header, rows):
if any(len(row) != len(header) for row in rows):
raise ValueError('Column length must be equal to headers')
column_widths = [len(field) for field in header]
for row in rows:
for i, field in enumerate(row):
column_widths[i] = max(len(str(field)),... | null |
23,373 | import os
import shutil
import json
import sys
import numpy as np
from .log import log_or_print
from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP
def copy_folder_files(new_dir, old_dir):
def force_create_dir(dir_name, copy_from_dir=None):
if os.path.exists(dir_name):
shutil.rmtree(dir_name)
os.makedirs(dir_... | null |
23,374 | import os
import shutil
import json
import sys
import numpy as np
from .log import log_or_print
from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP
def create_work_dir(dir_name):
if not os.path.exists(dir_name):
os.makedirs(dir_name) | null |
23,383 | import sys
import os
import logging
import io
from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP, NNDCT_DEBUG_LVL
def obj_to_str(obj):
def nndct_debug_print(string, title='', level=1):
def nndct_details_debug(obj, title, level=NNDCT_DEBUG_LVL.DETAILS):
nndct_debug_print(
"\n********************* <Start : {}>... | null |
23,391 | import math
from nndct_shared.base import NNDCT_OP
def get_avgpool_dpu_coeff(kernel):
scale = 1.0
if kernel == [3, 3]:
scale = 9.0 * 7.0 / 64.0
elif kernel == [5, 5]:
scale = 25.0 * 10.0 / 256.0
elif kernel in [[6, 6], [3, 6], [6, 3]]:
scale = 36.0 * 7.0 / 256.0
elif kernel == [7, 7]:
scale =... | null |
23,392 | import h5py
import json
from nndct_shared.nndct_graph.base_tensor import Tensor
class GraphHDF5Saver():
def __init__(self, nndct_graph):
def get_node_config(self, node):
def get_model_config(self):
def save(self, hdf5_path):
def save_graph(nndct_graph, hdf5_path='graph.hdf5'):
GraphHDF5Saver(nndc... | null |
23,393 | import copy
import gc
import inspect
import json
import numpy as np
import os
import random
import tensorflow as tf
import types
from tensorflow.python.distribute import distribution_strategy_context as ds_context
from nndct_shared.pruning import errors
from nndct_shared.pruning import pruner as pruner_lib
from nndct_s... | null |
23,394 | import copy
import gc
import inspect
import json
import numpy as np
import os
import random
import tensorflow as tf
import types
from tensorflow.python.distribute import distribution_strategy_context as ds_context
from nndct_shared.pruning import errors
from nndct_shared.pruning import pruner as pruner_lib
from nndct_s... | null |
23,395 | import copy
import gc
import inspect
import json
import numpy as np
import os
import random
import tensorflow as tf
import types
from tensorflow.python.distribute import distribution_strategy_context as ds_context
from nndct_shared.pruning import errors
from nndct_shared.pruning import pruner as pruner_lib
from nndct_s... | null |
23,396 | import copy
import gc
import inspect
import json
import numpy as np
import os
import random
import tensorflow as tf
import types
from tensorflow.python.distribute import distribution_strategy_context as ds_context
from nndct_shared.pruning import errors
from nndct_shared.pruning import pruner as pruner_lib
from nndct_s... | Fill 0 in removed channels. |
23,397 | import copy
import gc
import inspect
import json
import numpy as np
import os
import random
import tensorflow as tf
import types
from tensorflow.python.distribute import distribution_strategy_context as ds_context
from nndct_shared.pruning import errors
from nndct_shared.pruning import pruner as pruner_lib
from nndct_s... | Remove dimensions by giving channels. |
23,398 | import copy
import gc
import inspect
import json
import numpy as np
import os
import random
import tensorflow as tf
import types
from tensorflow.python.distribute import distribution_strategy_context as ds_context
from nndct_shared.pruning import errors
from nndct_shared.pruning import pruner as pruner_lib
from nndct_s... | null |
23,399 | import inspect
import numpy as np
from tensorflow import keras
from nndct_shared.pruning import errors
from tf_nndct.pruning import pruning_impl
class PruneMaskedWeight(keras.layers.Wrapper):
"""This wrapper augments a keras layer so the weight tensor may be pruned.
This wrapper implements magnitude-based pruning o... | Recursively collect the prunable layers in the model. |
23,400 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow as tf
def assign(ref, value, name=None):
if hasattr(tf, 'assign'):
return tf.assign(ref, value, name=name)
else:
return ref.assign(value, name=name) | null |
23,401 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow as tf
The provided code snippet includes necessary dependencies for implementing the `initialize_variables` function. Write a Python function `def initialize_variables(testcase)` to solve the ... | Handle global variable initialization in TF 1.X. Arguments: testcase: instance of tf.test.TestCase |
23,402 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow as tf
def is_v1_apis():
return hasattr(tf, 'assign') | null |
23,403 | import sys
from tensorflow.python.eager import context
from tensorflow.python.util import nest
def make_quantized(base):
class Inspectable(base):
class Attr:
SavingOutputs = '_saving_outputs'
SavedOutputs = '_saved_outputs'
def __call__(self, *args, **kwargs):
outputs = super(Inspectable... | null |
23,404 | from tensorflow.python.ops.signal import fft_ops
def rfft(input_tensor, fft_length=None, name=None):
return fft_ops.rfft(input_tensor, fft_length, name) | null |
23,405 | from tensorflow.python.ops.signal import fft_ops
def irfft(input_tensor, fft_length=None, name=None):
return fft_ops.irfft(input_tensor, fft_length, name) | null |
23,406 | from tensorflow.python.ops.signal import fft_ops
def ifft(input, name=None):
return fft_ops.ifft(input, name) | null |
23,407 | from tensorflow.python.ops import array_ops
def gather(params, indices, axis=None, batch_dims=0, name=None):
return array_ops.gather_v2(
params, indices, axis=axis, batch_dims=batch_dims, name=name) | null |
23,408 | import numpy as np
import os
import tensorflow as tf
from collections import OrderedDict
from tensorflow.keras import activations
from tensorflow.keras import layers as keras_layers
from tensorflow.python.framework import dtypes as tf_dtypes
from tensorflow.python.util import nest
from tensorflow.python.util import tf_... | null |
23,409 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import tensorflow as tf
from google.protobuf import text_format
from tensorflow.core.framework import graph_pb2
from tf_nndct.graph import ops
from tf_nndct.utils import generic_utils
from tf_nndct.uti... | null |
23,410 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import tensorflow as tf
from google.protobuf import text_format
from tensorflow.core.framework import graph_pb2
from tf_nndct.graph import ops
from tf_nndct.utils import generic_utils
from tf_nndct.uti... | null |
23,411 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import tensorflow as tf
from google.protobuf import text_format
from tensorflow.core.framework import graph_pb2
from tf_nndct.graph import ops
from tf_nndct.utils import generic_utils
from tf_nndct.uti... | null |
23,412 | import json
import os
import tensorflow as tf
from tensorflow.keras import layers
from tensorflow.core.protobuf import config_pb2
from tensorflow.lite.python.util import run_graph_optimizations as _run_graph_optimizations
from tf_nndct.graph import OpTypes
from tf_nndct.graph import converter
from tf_nndct.graph import... | Get the keras layer the given op is generated from. Returns None if op does not belong to any layer. Trace back from current scope to parent scope recursively until it reaches the outermost scope. |
23,413 | import json
import os
import tensorflow as tf
from tensorflow.keras import layers
from tensorflow.core.protobuf import config_pb2
from tensorflow.lite.python.util import run_graph_optimizations as _run_graph_optimizations
from tf_nndct.graph import OpTypes
from tf_nndct.graph import converter
from tf_nndct.graph import... | Get layer's inbound nodes. The config of a layer does not include connectivity information, nor the layer class name. These are handled by keras.Model. So we extract them from model's config and associate them to the corresponding layer. |
23,414 | import imp
from tensorflow import keras
from tensorflow.python.ops import array_ops
from tensorflow.python.util import nest
from nndct_shared.pruning import pruning_lib
from tf_nndct.graph import OpTypes
from tf_nndct.graph import parser
from tf_nndct.graph import utils
from tf_nndct.graph import writer as writer_lib
f... | null |
23,415 | import numpy as np
from enum import Enum
from tensorflow.core.framework import types_pb2
def from_numpy(dtype):
return _NP_TO_NNDCT[dtype] | null |
23,416 | import numpy as np
from enum import Enum
from tensorflow.core.framework import types_pb2
_NNDCT_TO_NP = {
DType.FLOAT: np.float32,
DType.FLOAT16: np.float16,
DType.DOUBLE: np.float64,
DType.INT32: np.int32,
DType.INT16: np.int16,
DType.INT8: np.int8,
DType.UINT8: np.uint8,
DType.UINT16: ... | null |
23,417 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import copy
import numpy as np
import tensorflow as tf
from tensorflow.keras import activations
from tensorflow.keras import layers
from tensorflow.python.util import nest
from tf_nndct.graph import OpTypes
from... | null |
23,418 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import copy
import numpy as np
import tensorflow as tf
from tensorflow.keras import activations
from tensorflow.keras import layers
from tensorflow.python.util import nest
from tf_nndct.graph import OpTypes
from... | null |
23,419 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import copy
import numpy as np
import tensorflow as tf
from tensorflow.keras import activations
from tensorflow.keras import layers
from tensorflow.python.util import nest
from tf_nndct.graph import OpTypes
from... | null |
23,420 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import copy
import numpy as np
import tensorflow as tf
from tensorflow.keras import activations
from tensorflow.keras import layers
from tensorflow.python.util import nest
from tf_nndct.graph import OpTypes
from... | null |
23,421 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import copy
import numpy as np
import tensorflow as tf
from tensorflow.keras import activations
from tensorflow.keras import layers
from tensorflow.python.util import nest
from tf_nndct.graph import OpTypes
from... | null |
23,422 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import copy
import numpy as np
import tensorflow as tf
from tensorflow.keras import activations
from tensorflow.keras import layers
from tensorflow.python.util import nest
from tf_nndct.graph import OpTypes
from... | null |
23,423 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import copy
import numpy as np
import tensorflow as tf
from tensorflow.keras import activations
from tensorflow.keras import layers
from tensorflow.python.util import nest
from tf_nndct.graph import OpTypes
from... | null |
23,424 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import copy
import numpy as np
import tensorflow as tf
from tensorflow.keras import activations
from tensorflow.keras import layers
from tensorflow.python.util import nest
from tf_nndct.graph import OpTypes
from... | Convert layers.Normalization to GeTFNormalizationneric |
23,425 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import copy
import numpy as np
import tensorflow as tf
from tensorflow.keras import activations
from tensorflow.keras import layers
from tensorflow.python.util import nest
from tf_nndct.graph import OpTypes
from... | Convert layers.Rescaling to TFRescaling |
23,426 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import copy
import numpy as np
import tensorflow as tf
from tensorflow.keras import activations
from tensorflow.keras import layers
from tensorflow.python.util import nest
from tf_nndct.graph import OpTypes
from... | null |
23,427 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import copy
import numpy as np
import tensorflow as tf
from tensorflow.keras import activations
from tensorflow.keras import layers
from tensorflow.python.util import nest
from tf_nndct.graph import OpTypes
from... | null |
23,428 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import copy
import numpy as np
import tensorflow as tf
from tensorflow.keras import activations
from tensorflow.keras import layers
from tensorflow.python.util import nest
from tf_nndct.graph import OpTypes
from... | null |
23,429 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import copy
import numpy as np
import tensorflow as tf
from tensorflow.keras import activations
from tensorflow.keras import layers
from tensorflow.python.util import nest
from tf_nndct.graph import OpTypes
from... | null |
23,430 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import copy
import numpy as np
import tensorflow as tf
from tensorflow.keras import activations
from tensorflow.keras import layers
from tensorflow.python.util import nest
from tf_nndct.graph import OpTypes
from... | null |
23,431 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import copy
import numpy as np
import tensorflow as tf
from tensorflow.keras import activations
from tensorflow.keras import layers
from tensorflow.python.util import nest
from tf_nndct.graph import OpTypes
from... | null |
23,432 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import copy
import numpy as np
import tensorflow as tf
from tensorflow.keras import activations
from tensorflow.keras import layers
from tensorflow.python.util import nest
from tf_nndct.graph import OpTypes
from... | null |
23,433 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import copy
import numpy as np
import tensorflow as tf
from tensorflow.keras import activations
from tensorflow.keras import layers
from tensorflow.python.util import nest
from tf_nndct.graph import OpTypes
from... | null |
23,434 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import copy
import numpy as np
import tensorflow as tf
from tensorflow.keras import activations
from tensorflow.keras import layers
from tensorflow.python.util import nest
from tf_nndct.graph import OpTypes
from... | null |
23,435 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import copy
import numpy as np
import tensorflow as tf
from tensorflow.keras import activations
from tensorflow.keras import layers
from tensorflow.python.util import nest
from tf_nndct.graph import OpTypes
from... | null |
23,436 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import copy
import numpy as np
import tensorflow as tf
from tensorflow.keras import activations
from tensorflow.keras import layers
from tensorflow.python.util import nest
from tf_nndct.graph import OpTypes
from... | null |
23,437 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import copy
import numpy as np
import tensorflow as tf
from tensorflow.keras import activations
from tensorflow.keras import layers
from tensorflow.python.util import nest
from tf_nndct.graph import OpTypes
from... | null |
23,438 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import copy
import numpy as np
import tensorflow as tf
from tensorflow.keras import activations
from tensorflow.keras import layers
from tensorflow.python.util import nest
from tf_nndct.graph import OpTypes
from... | null |
23,439 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import copy
import numpy as np
import tensorflow as tf
from tensorflow.keras import activations
from tensorflow.keras import layers
from tensorflow.python.util import nest
from tf_nndct.graph import OpTypes
from... | null |
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