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summary handle not a image tensor

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pull/1143/head
李鸿章 5 years ago
parent 979d2e23dc
commit 324195280c
1 changed files with 53 additions and 61 deletions
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114
mindspore/train/summary/_summary_adapter.py
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@ -117,19 +117,19 @@ def package_summary_event(data_list, step):
summary_value.tag = tag
# get the summary type and parse the tag
if summary_type == 'Scalar':
summary_value.scalar_value = _get_scalar_summary(tag, data)
if not _fill_scalar_summary(tag, data, summary_value):
del summary.value[-1]
elif summary_type == 'Tensor':
summary_tensor = summary_value.tensor
_get_tensor_summary(tag, data, summary_tensor)
_fill_tensor_summary(tag, data, summary_value.tensor)
elif summary_type == 'Image':
summary_image = summary_value.image
_get_image_summary(tag, data, summary_image, MS_IMAGE_TENSOR_FORMAT)
if not _fill_image_summary(tag, data, summary_value.image, MS_IMAGE_TENSOR_FORMAT):
del summary.value[-1]
elif summary_type == 'Histogram':
summary_histogram = summary_value.histogram
_fill_histogram_summary(tag, data, summary_histogram)
_fill_histogram_summary(tag, data, summary_value.histogram)
else:
# The data is invalid ,jump the data
logger.error("Summary type(%r) is error, tag = %r", summary_type, tag)
del summary.value[-1]
return summary_event
@ -173,7 +173,7 @@ def _nptype_to_prototype(np_value):
return proto
def _get_scalar_summary(tag: str, np_value):
def _fill_scalar_summary(tag: str, np_value, summary):
"""
Package the scalar summary.
@ -185,25 +185,20 @@ def _get_scalar_summary(tag: str, np_value):
Summary, return scalar summary content.
"""
logger.debug("Set(%r) the scalar summary value", tag)
if np_value.ndim == 0:
if np_value.size == 1:
# is scalar
scalar_value = np_value.item()
elif np_value.ndim == 1:
# Because now GE can't providesumm the real shape info to convert the Tensor
# So consider the dim = 1, shape = (1,) tensor is scalar
scalar_value = np_value[0]
if np_value.shape != (1,):
logger.error("The tensor is not Scalar, tag = %r, Shape = %r", tag, np_value.shape)
else:
np_list = np_value.reshape(-1).tolist()
scalar_value = np_list[0]
logger.error("The value is not Scalar, tag = %r, ndim = %r", tag, np_value.ndim)
logger.debug("The tag(%r) value is: %r", tag, scalar_value)
return scalar_value
def _get_tensor_summary(tag: str, np_value, summary_tensor):
summary.scalar_value = np_value.item()
return True
if np_value.size > 1:
logger.warning("The tensor is not a single scalar, tag = %r, ndim = %r, shape = %r", tag, np_value.ndim,
np_value.shape)
summary.scalar_value = next(np_value.flat).item()
return True
logger.error("There no values inside tensor, tag = %r, size = %r", tag, np_value.size)
return False
def _fill_tensor_summary(tag: str, np_value, summary_tensor):
"""
Package the tensor summary.
@ -287,12 +282,18 @@ def _fill_histogram_summary(tag: str, np_value: np.ndarray, summary) -> None:
logger.warning('There are no valid values in the ndarray(size=%d, shape=%d)', total, np_value.shape)
# summary.{min, max, sum} are 0s by default, no need to explicitly set
else:
summary.min = ma_value.min()
summary.max = ma_value.max()
summary.sum = ma_value.sum()
# BUG: max of a masked array with dtype np.float16 returns inf
# See numpy issue#15077
if issubclass(np_value.dtype.type, np.floating):
summary.min = ma_value.min(fill_value=np.PINF)
summary.max = ma_value.max(fill_value=np.NINF)
else:
summary.min = ma_value.min()
summary.max = ma_value.max()
summary.sum = ma_value.sum(dtype=np.float64)
bins = _calc_histogram_bins(valid)
range_ = summary.min, summary.max
hists, edges = np.histogram(np_value, bins=bins, range=range_)
bins = np.linspace(summary.min, summary.max, bins + 1, dtype=np_value.dtype)
hists, edges = np.histogram(np_value, bins=bins)
for hist, edge1, edge2 in zip(hists, edges, edges[1:]):
bucket = summary.buckets.add()
@ -301,7 +302,7 @@ def _fill_histogram_summary(tag: str, np_value: np.ndarray, summary) -> None:
bucket.left = edge1
def _get_image_summary(tag: str, np_value, summary_image, input_format='NCHW'):
def _fill_image_summary(tag: str, np_value, summary_image, input_format='NCHW'):
"""
Package the image summary.
@ -315,8 +316,14 @@ def _get_image_summary(tag: str, np_value, summary_image, input_format='NCHW'):
Summary, return image summary content.
"""
logger.debug("Set(%r) the image summary value", tag)
if np_value.ndim != 4:
logger.error("The value is not Image, tag = %r, ndim = %r", tag, np_value.ndim)
if np_value.ndim != 4 or np_value.shape[1] not in (1, 3):
logger.error("The value is not Image, tag = %r, ndim = %r, shape=%r", tag, np_value.ndim, np_value.shape)
return False
if np_value.ndim != len(input_format):
logger.error("The tensor with dim(%r) can't convert the format(%r) because dim not same", np_value.ndim,
input_format)
return False
# convert the tensor format
tensor = _convert_image_format(np_value, input_format)
@ -337,7 +344,7 @@ def _get_image_summary(tag: str, np_value, summary_image, input_format='NCHW'):
summary_image.width = width
summary_image.colorspace = channel
summary_image.encoded_image = image_string
return summary_image
return True
def _make_image(tensor, rescale=1):
@ -376,30 +383,21 @@ def _convert_image_format(np_tensor, input_format, out_format='HWC'):
Returns:
Tensor, return format image.
"""
out_tensor = None
if np_tensor.ndim != len(input_format):
logger.error("The tensor with dim(%r) can't convert the format(%r) because dim not same", np_tensor.ndim,
input_format)
return out_tensor
input_format = input_format.upper()
if len(input_format) == 4:
# convert the NCHW
if input_format != 'NCHW':
index = [input_format.find(c) for c in 'NCHW']
tensor_nchw = np_tensor.transpose(index)
else:
tensor_nchw = np_tensor
# convert the NCHW
if input_format != 'NCHW':
index = [input_format.find(c) for c in 'NCHW']
tensor_nchw = np_tensor.transpose(index)
else:
tensor_nchw = np_tensor
# make grid to expand N
tensor_chw = _make_canvas_for_imgs(tensor_nchw)
# make grid to expand N
tensor_chw = _make_canvas_for_imgs(tensor_nchw)
# convert to out format
out_index = ['CHW'.find(c) for c in out_format]
out_tensor = tensor_chw.transpose(out_index)
else:
logger.error("Don't support the format(%r) convert", input_format)
# convert to out format
out_index = ['CHW'.find(c) for c in out_format]
out_tensor = tensor_chw.transpose(out_index)
return out_tensor
@ -415,15 +413,9 @@ def _make_canvas_for_imgs(tensor, col_imgs=8):
Tensor, retrun canvas of image.
"""
# expand the N1HW to N3HW
out_canvas = None
if tensor.shape[1] == 1:
tensor = np.concatenate([tensor, tensor, tensor], 1)
# check the tensor format
if tensor.ndim != 4 or tensor.shape[1] != 3:
logger.error("The image tensor with ndim(%r) and shape(%r) is not 'NCHW' format", tensor.ndim, tensor.shape)
return out_canvas
# expand the N
n = tensor.shape[0]
h = tensor.shape[2]

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