clean_0720_master
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@ -28,6 +28,7 @@ from mindspore.common import dtype as mstype
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from mindspore._c_expression import Tensor as Tensor_
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class Rel(Enum):
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"""Numerical relationship between variables, logical relationship enumeration definition of range."""
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# scalar compare
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EQ = 1 # ==
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@ -643,7 +643,8 @@ def set_context(**kwargs):
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a file by default, and turns off printing to the screen. If the file already exists, add a timestamp
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suffix to the file. Default: ''.
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enable_sparse (bool): Whether to enable sparsity feature. Default: False.
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For details of sparsity and sparse tensor, please check `<https://www.mindspore.cn/doc/programming_guide/zh-CN/master/tensor.html>`_.
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For details of sparsity and sparse tensor, please check
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`<https://www.mindspore.cn/doc/programming_guide/zh-CN/master/tensor.html>`_.
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max_call_depth (int): Specify the maximum depth of function call. Must be positive integer. Default: 1000.
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env_config_path (str): Config path for DFX.
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auto_tune_mode (str): The mode of auto tune when op building, get the best tiling performance,
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@ -290,6 +290,7 @@ def _get_env_config():
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return config_dict
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def _verify_config(kwargs):
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"""
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Verify log configurations.
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@ -27,7 +27,8 @@ try:
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ms = import_module("mindspore")
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except ModuleNotFoundError:
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ms = None
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finally:
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pass
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def _check_mul():
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"""
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@ -65,3 +66,5 @@ def run_check():
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except Exception as e:
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print("MindSpore running check failed.")
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print(str(e))
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finally:
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pass
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@ -97,6 +97,8 @@ def _make_directory(path: str):
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except PermissionError as e:
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logger.error("No write permission on the directory(%r), error = %r", path, e)
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raise TypeError("No write permission on the directory.")
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finally:
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pass
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return real_path
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@ -238,6 +240,8 @@ def read_proto(file_name, proto_format="MINDIR", display_data=False):
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except BaseException as e:
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logger.error("Failed to read the file `%s`, please check the correct of the file.", file_name)
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raise ValueError(e.__str__())
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finally:
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pass
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if proto_format == "MINDIR" and not display_data:
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for param_proto in model.graph.parameter:
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@ -23,6 +23,7 @@ from mindspore.train.summary.summary_record import _cache_summary_tensor_data
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_cur_net = None
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def set_cur_net(net):
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"""
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Set current net for which we are using to save checkpoint.
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