def tensor_comparisons(self,
name,
shape,
detail='data',
tolerance='0',
rank_id=0,
graph_name=None):
"""
Get tensor comparisons data for given name, detail, shape and tolerance.
Args:
name (str): The name of tensor for ui.
shape (str): Specify concrete dimensions of shape.
detail (str): Specify which data to query. Current available value is 'data' which means
concrete tensor data. Histogram or unique count can be supported in the future.
rank_id (int): The id of rank. Default: 0.
tolerance (str): Specify tolerance of difference between current step tensor and previous
step tensor. Default value is 0.
graph_name (str): The graph name. Default: None.
Returns:
dict, the retrieved data.
"""
if self.cache_store.get_stream_handler(
Streams.METADATA).state != ServerStatus.WAITING.value:
log.error(
"Failed to compare tensors as the MindSpore is not in waiting state."
)
raise DebuggerCompareTensorError(
"Failed to compare tensors as the MindSpore is not in waiting state."
)
self.validate_tensor_param(name, detail)
# Limit to query max two dimensions for tensor in table view.
parsed_shape = TensorUtils.parse_shape(shape,
limit=MAX_DIMENSIONS_FOR_TENSOR)
node_type, tensor_name, graph_name = self._get_tensor_name_and_type_by_ui_name(
name, graph_name, rank_id)
tolerance = to_float(tolerance, 'tolerance')
tensor_stream = self.cache_store.get_stream_handler(
Streams.TENSOR).get_tensor_handler_by_rank_id(rank_id)
cur_step = self.cache_store.get_stream_handler(Streams.METADATA).step
if node_type == NodeTypeEnum.PARAMETER.value:
reply = tensor_stream.get_tensors_diff(tensor_name, parsed_shape,
tolerance, cur_step)
else:
raise DebuggerParamValueError(
"The node type must be parameter, but got {}.".format(
node_type))
if reply.pop('view_cmd', False):
self._send_view_cmd(name, graph_name, rank_id, tensor_name,
node_type)
return reply
def tensor_comparisons(self, name, shape, detail='data', tolerance='0'):
"""
Get tensor comparisons data for given name, detail, shape and tolerance.
Args:
name (str): The name of tensor for ui.
detail (str): Specify which data to query. Current available value is 'data' which means
concrete tensor data. Histogram or unique count can be supported in the future.
shape (str): Specify concrete dimensions of shape.
tolerance (str): Specify tolerance of difference between current step tensor and previous
step tensor. Default value is 0.
Raises:
DebuggerParamValueError, If node type is not parameter or value of detail is not support.
DebuggerCompareTensorError, If MindSpore is not in waiting state.
Returns:
dict, the retrieved data.
"""
if self.cache_store.get_stream_handler(
Streams.METADATA).state != ServerStatus.WAITING.value:
log.error(
"Failed to compare tensors as the MindSpore is not in waiting state."
)
raise DebuggerCompareTensorError(
"Failed to compare tensors as the MindSpore is not in waiting state."
)
self.validate_tensor_param(name, detail)
parsed_shape = self.parse_shape(shape)
node_type, tensor_name = self._get_tensor_name_and_type_by_ui_name(
name)
tolerance = to_float(tolerance, 'tolerance')
tensor_stream = self.cache_store.get_stream_handler(Streams.TENSOR)
if detail == 'data':
if node_type == NodeTypeEnum.PARAMETER.value:
reply = tensor_stream.get_tensors_diff(tensor_name,
parsed_shape, tolerance)
else:
raise DebuggerParamValueError(
"The node type must be parameter, but got {}.".format(
node_type))
else:
raise DebuggerParamValueError(
"The value of detail: {} is not support.".format(detail))
return reply