id int64 0 190k | prompt stringlengths 21 13.4M | docstring stringlengths 1 12k ⌀ |
|---|---|---|
23,126 | 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 |
23,127 | 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 |
23,128 | from collections import deque
def graph_search_handler(start_node,
generator,
frontier,
handler=None,
gen_params={}):
class FIFOQueue(Queue):
def __init__(self):
def append(self, item):
def __len__(self):
... | null |
23,129 | 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 reset_group_members(graph, groups,... | null |
23,130 | 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 glue_group_members(graph, groups, s... | null |
23,131 | 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 reorder_multi_subgraph_nodes(graph... | null |
23,132 | 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 merge_multi_subgraphs(graphs: List... | null |
23,133 | 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 |
23,134 | 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_block_node_to_graph(block_... | null |
23,135 | import json
import numpy as np
from collections import OrderedDict
from enum import Enum, auto
from functools import partial
from typing import Dict, List, Callable, Optional, Union, Any, Set
from nndct_shared.nndct_graph.base_tensor import Tensor
from nndct_shared.utils.common import AutoName
The provided code snippe... | r""" if in_out == 0 stamp value in memory, otherwise get memory_value |
23,136 | import copy
from collections import defaultdict, deque, namedtuple
from typing import List
from nndct_shared.quantization import BaseQuantizer
from nndct_shared.base import NNDCT_OP
from nndct_shared.nndct_graph import Graph, Node, Tensor, GraphSearcher
from nndct_shared.nndct_graph import operator_definition as base_o... | null |
23,137 | 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 |
23,138 | 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 |
23,139 | 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 |
23,140 | 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... | r""" nndct reshape is a macro operator, including pack, reshape |
23,141 | 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... | resize is a macro operator, including concat , resize |
23,142 | 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 |
23,143 | 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 |
23,144 | 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 |
23,145 | 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 |
23,146 | 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 |
23,147 | 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 |
23,148 | 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 |
23,149 | 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 |
23,150 | 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 |
23,151 | from nndct_shared.base import NNDCT_CONSTANT
def shape_attr_transform_fn(node, transpose_order):
shape = node.node_attr(node.op.AttrName.SHAPE)
new_shape = len(shape) * [None]
for i, dim in enumerate(transpose_order):
new_shape[i] = shape[dim]
node.set_node_attr(node.op.AttrName.SHAPE, new_shape) | null |
23,152 | from nndct_shared.base import NNDCT_CONSTANT
def axis_attr_transform_fn(node, transpose_order):
dim = node.node_attr(node.op.AttrName.AXIS)
new_dim = transpose_order.index(dim)
node.set_node_attr(node.op.AttrName.AXIS, new_dim) | null |
23,153 | from nndct_shared.base import NNDCT_CONSTANT
def slice_attr_transform_fn(node, transpose_order):
begin = node.node_attr(node.op.AttrName.BEGIN)
new_begin = [None] * len(begin)
for dim, pos in enumerate(begin):
new_dim = transpose_order.index(dim)
new_begin[new_dim] = pos
begin_mask =... | null |
23,154 | from nndct_shared.base import NNDCT_CONSTANT
def reduce_op_attr_transform_fn(node, transpose_order):
dims = node.node_attr(node.op.AttrName.DIMS)
new_dims = [None] * len(dims)
for i, dim in enumerate(dims):
new_dim = transpose_order.index(dim)
new_dims[i] = new_dim
node.set_node_attr(node.op.AttrN... | null |
23,155 | from collections import defaultdict
from nndct_shared.utils import NndctDebugLogger, NndctOption
def convert_quant_config_to_dict(quant_config, init=False):
config = {'param': defaultdict(list), 'output': defaultdict(list), 'input': defaultdict(list)}
for key in quant_config.get_output_keys():
for quant_info i... | null |
23,156 | from collections import defaultdict
from nndct_shared.utils import NndctDebugLogger, NndctOption
NNDCTIR2XIR_CONVERTOR = {
# NNDCT op type: (XIR op type , XIR_CONVERT_FUNCTION)
NNDCT_OP.INPUT: ("data", data_xop),
NNDCT_OP.CONV1D: ("conv1d", to_xir("conv1d")),
NNDCT_OP.CONV2D: ("conv2d", to_xir("conv2d"... | null |
23,157 | 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 |
23,158 | 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 XIRHelper(object):
def f... | null |
23,159 | 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 |
23,160 | 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 __init__... | null |
23,161 | 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 |
23,162 | 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 |
23,163 | 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 |
23,164 | 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 |
23,165 | 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 |
23,166 | 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 |
23,167 | 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 |
23,168 | 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 |
23,169 | 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 kernel_need_quant(quantizer, node):
if NndctOption.nndct_quant_off.value:
... | null |
23,170 | 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 |
23,171 | 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 is_quant_end_point(graph, node, quant_types):
if len(graph.parents(node.name))... | null |
23,172 | 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 get_flows_and_info(quant_mode,
quantizer,
... | null |
23,173 | 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):
quantizer = quantizer or GLOBAL_MAP.get_el... | null |
23,174 | 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):
quantizer = quantizer or GLOBAL_MAP.get_el... | null |
23,175 | 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):
quantizer = quantizer or GLOBAL_MAP.get_el... | null |
23,176 | import numpy as np
import math
def max(data, name='', quantizer=None):
return data.max() | null |
23,177 | import numpy as np
import math
def min(data, name='', quantizer=None):
return data.min() | null |
23,178 | import numpy as np
import math
def quant_diff_s(data, bitwidth, range, round_method=2, name='',
quantizer=None):
raise NotImplementedError("please implement the diffs operation") | null |
23,179 | import numpy as np
import math
def nonlin(data, alpha, signed):
if signed:
return np.clip(data, -alpha, alpha)
else:
return np.clip(data, 0, alpha) | null |
23,180 | import numpy as np
import math
def pact_quant_neuron(data,
bitw,
bita,
alpha_init_value=None,
signed=False,
trainable=True,
warmup=False,
name='',
... | null |
23,181 | import numpy as np
import math
def graffitist_quant_neuron(data, bn, fp, method=2, name=''):
raise NotImplementedError(
"please implement the lowbit_quant_neuron operation") | null |
23,182 | 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 |
23,183 | 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 |
23,184 | 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 DataFormat(object):
channel_firs... | NC* -> N*C/ N*C ->NC* |
23,185 | 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
def permute_data(data, order):
if ord... | null |
23,186 | 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
def permute_axes(axes, order):
if ord... | null |
23,187 | 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
def combine_orders(order1, order2):
n... | null |
23,188 | 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 |
23,189 | 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 |
23,190 | 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... | Return how much logging output will be produced. |
23,191 | 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... | Sets the threshold for what messages will be logged. |
23,192 | 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 |
23,193 | def set_kwargs_or_defaults(obj, kwargs, default_attrs=None, keys=None):
if default_attrs:
keys = keys or default_attrs.keys()
attrs_dict = get_kwargs_or_defaults(kwargs, default_attrs, keys)
else:
keys = keys or kwargs.keys()
attrs_dict = kwargs
for k, v in attrs_dict.items():
setattr(obj, k, ... | null |
23,194 |
def not_implement(func):
def wrapper(obj, *args, **kwargs):
func(obj, *args, **kwargs)
raise NotImplemented("{} {}".format(obj, func.__name__))
return wrapper | null |
23,195 | import numpy as np
from nndct_shared.base import NNDCT_OP
def get_batchnorm_params(param_list, param_getter, center=True, scale=True):
#order: gamma,beta,mean,var
if all(param_getter(p) is not None for p in param_list):
param_shape = param_getter(param_list[-1]).shape
bn_params = []
if center and scale... | null |
23,196 | import numpy as np
from nndct_shared.base import NNDCT_OP
def get_batchnorm_param_names(param_list, center=True, scale=True):
if center and scale:
assert len(
param_list) == 4, "expect 4 parameters names, got " + str(param_list)
return {
'gamma': param_list[0],
'beta': param_list[1],
... | null |
23,197 | import numpy as np
from nndct_shared.base import NNDCT_OP
def get_in_out_channel_idx(ndim, optype, data_formats):
#TODO: same shape with different format, is this possible?
if ndim == 1:
return 0, 0
if optype == NNDCT_OP.CONV2D:
if data_formats[optype] == 'HWIO':
in_idx, out_idx = 2, 3
elif data... | null |
23,198 | import numpy as np
from nndct_shared.base import NNDCT_OP
def get_in_out_channel_idx(ndim, optype, data_formats):
#TODO: same shape with different format, is this possible?
if ndim == 1:
return 0, 0
if optype == NNDCT_OP.CONV2D:
if data_formats[optype] == 'HWIO':
in_idx, out_idx = 2, 3
elif data... | null |
23,199 | import numpy as np
from nndct_shared.base import NNDCT_OP
def delete_in_out_channel_indexs(data,
in_idx=None,
out_idx=None,
in_channel_array=None,
out_channel_array=None):
if in_idx is ... | null |
23,200 | import numpy as np
from nndct_shared.base import NNDCT_OP
def insert_in_out_channel_indexs(data,
in_idx=None,
out_idx=None,
in_channel_array=None,
out_channel_array=None):
if in_idx is ... | null |
23,201 | import numpy as np
from nndct_shared.base import NNDCT_OP
def expand_in_out_channel_indexs(data,
in_idx=None,
out_idx=None,
in_channel_array=None,
out_channel_array=None):
# assert len(... | null |
23,202 | 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 |
23,203 | 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 |
23,204 | from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP, NNDCT_DEBUG_LVL
from .log import nndct_debug_print
def get_split_sym(model_type):
if model_type == 'Nndct':
return '_'
elif model_type in ['tensorflow', 'tf-keras']:
return '/'
elif model_type == 'torch':
return '.'
raise Exception("can not find... | null |
23,205 | from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP, NNDCT_DEBUG_LVL
from .log import nndct_debug_print
def default_scoped_name(obj):
if isinstance(obj, str):
name = obj
else:
name = obj.name
return '/'.join(name.split('/')[:-1]), name.split('/')[-1] | null |
23,206 | from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP, NNDCT_DEBUG_LVL
from .log import nndct_debug_print
def get_default_name(obj):
if isinstance(obj, str):
return obj
name = getattr(obj, 'name', None)
if not name:
raise Exception("{} has no attribute name, please check!".format(obj))
return name.split... | null |
23,207 | from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP, NNDCT_DEBUG_LVL
from .log import nndct_debug_print
def default_legal_name(name):
return name.replace('.', 'DOT').replace('/', 'SPL') | null |
23,208 | from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP, NNDCT_DEBUG_LVL
from .log import nndct_debug_print
def derive_scope_name(name, scope, split_sym, offset=0):
name_list = name.split(split_sym)
for idx in range(len(name_list)):
if name_list[idx].startswith(scope):
base_idx = idx
break
return sp... | null |
23,209 | from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP, NNDCT_DEBUG_LVL
from .log import nndct_debug_print
def reverse_default_legal_name(name):
return name.replace('DOT', '.').replace('SPL', '/') | null |
23,210 | from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP, NNDCT_DEBUG_LVL
from .log import nndct_debug_print
def remove_suffix(obj, suffix):
if obj is None:
return obj
if suffix is None or suffix == '':
return obj
if isinstance(suffix, str):
if isinstance(obj, str) and len(suffix) > 0 and obj.endswith(su... | null |
23,211 | 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):
def scoped_untrans_name(name, scp):
org_name = remove_trans_scp_prefix(name, scp)
return scp + org_name | null |
23,212 | from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP, NNDCT_DEBUG_LVL
from .log import nndct_debug_print
def remove_prefix(obj, prefix):
def scoped_trans_name(name, scp):
org_name = remove_prefix(name, scp)
if org_name.startswith(NNDCT_KEYS.TRANS_SCOPE):
return scp + org_name
else:
return scp + NNDCT_KEY... | null |
23,213 | 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):
GLOBAL_MAP = GlobalMap()
def nndct_debug_print(string, title='', level=1):
def map_output_and_node(output, node_or_name, model_type):
if node_or_name is None:
re... | null |
23,214 | from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP, NNDCT_DEBUG_LVL
from .log import nndct_debug_print
GLOBAL_MAP = GlobalMap()
def node_from_output(output_name, model_type):
if model_type == 'Nndct':
return output_name
if model_type == 'tensorflow':
output_name = output_name.split(':')[0]
elif model_... | null |
23,215 | from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP, NNDCT_DEBUG_LVL
from .log import nndct_debug_print
GLOBAL_MAP = GlobalMap()
def get_output_from_node(node_name, idx=-1):
node_map = GLOBAL_MAP.get_ele(NNDCT_KEYS.NODE_TO_OUTPUT_MAP)
if node_map and node_name in node_map:
return node_map[node_name][idx]
r... | null |
23,216 | from nndct_shared.base import NNDCT_KEYS, GLOBAL_MAP, NNDCT_DEBUG_LVL
from .log import nndct_debug_print
GLOBAL_MAP = GlobalMap()
def get_all_outputs_from_node(node_name):
node_map = GLOBAL_MAP.get_ele(NNDCT_KEYS.NODE_TO_OUTPUT_MAP)
if node_map and node_name in node_map:
return node_map[node_name]
return no... | null |
23,217 | 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 to_des_dict(dicts, as_des=True, extra_types={}):
assert isinstance(dicts,list) and all(isinstance(d,dict) for d in dicts),\
"dicts should be list of dictionari... | null |
23,218 | 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 check_diff(matA, matB, nameA, nameB, error, with_msg=True):
is_pass = True
mat = matA - matB
mat = mat / np.sqrt(matA**2 + error)
title = "{:25} VS {:25} : ".... | null |
23,219 | 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 to_jsonstr(obj, pre_space=2):
def _json_lst_str(lst):
string = ""
for idx in range(len(lst)):
if isinstance(lst[idx], str):
string += '"{}",'... | null |
23,220 | 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 load_json_obj(file_or_obj):
if isinstance(file_or_obj, str):
with open(file_or_obj, 'r') as f:
obj = json.load(f)
elif isinstance(file_or_obj, dict):
... | null |
23,221 | 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 dpu_format_print(mat):
flatten_mat = mat.reshape(mat.size)
cnt = 0
while cnt < len(flatten_mat):
print(("{:0>2x}" * 16).format(*tuple(flatten_mat[cnt:cnt + ... | null |
23,222 | 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):
for file_name in os.listdir(old_dir):
full_file_name = os.path.join(old_dir, file_name)
if (os.path.isfile(full_file_nam... | null |
23,223 | 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_center_edge(string, to_str=False, blank_line=0, width=120):
center_str = "{0}>>{1:40}<<{0}".format("=" * 30,
string.c... | null |
23,224 | 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 log_or_print(str, logger=None):
if logger:
logger.info(str)
else:
print(str)
def basic_info(mat, name=None, logger=None, to_str=False):
if isinstance(m... | null |
23,225 | 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_csv_format(mat):
assert mat.ndim == 2
for row in range(mat.shape[0]):
for col in range(mat.shape[1]):
print(str(mat[row, col]) + ',', end='')
... | null |
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