def concatenate(tensors, axis=-1):
"""Concatenates a list of tensors alongside the specified axis.
# Returns
A tensor.
"""
if axis < 0:
dims = ndim(tensors[0])
if dims:
axis = axis % dims
else:
axis = 0
if py_all([is_sparse(x) for x in tensors]):
return tf.sparse_concat(axis, tensors)
else:
if tf_major_version >= 1:
return tf.concat([to_dense(x) for x in tensors], axis)
else:
try:
return tf.concat_v2([to_dense(x) for x in tensors], axis)
except AttributeError:
return tf.concat(axis, [to_dense(x) for x in tensors])
python类sparse_concat()的实例源码
tensorflow_backend.py 文件源码
项目：deep-learning-keras-projects
作者: jasmeetsb
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文件源码
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def concatenate(tensors, axis=-1):
'''Concatenates a list of tensors alongside the specified axis.
'''
if axis < 0:
dims = ndim(tensors[0])
if dims:
axis = axis % dims
else:
axis = 0
if py_all([is_sparse(x) for x in tensors]):
return tf.sparse_concat(axis, tensors)
else:
try:
return tf.concat_v2([to_dense(x) for x in tensors], axis)
except AttributeError:
return tf.concat(axis, [to_dense(x) for x in tensors])
def concatenate(tensors, axis=-1):
"""Concatenates a list of tensors alongside the specified axis.
# Returns
A tensor.
"""
if axis < 0:
dims = ndim(tensors[0])
if dims:
axis = axis % dims
else:
axis = 0
if py_all([is_sparse(x) for x in tensors]):
return tf.sparse_concat(axis, tensors)
else:
if tf_major_version >= 1:
return tf.concat([to_dense(x) for x in tensors], axis)
else:
try:
return tf.concat_v2([to_dense(x) for x in tensors], axis)
except AttributeError:
return tf.concat(axis, [to_dense(x) for x in tensors])
def concatenate(tensors, axis=-1):
"""Concatenates a list of tensors alongside the specified axis.
# Arguments
tensors: list of tensors to concatenate.
axis: concatenation axis.
# Returns
A tensor.
"""
if axis < 0:
rank = ndim(tensors[0])
if rank:
axis %= rank
else:
axis = 0
if py_all([is_sparse(x) for x in tensors]):
return tf.sparse_concat(axis, tensors)
else:
return tf.concat([to_dense(x) for x in tensors], axis)
def concatenate(tensors, axis=-1):
'''Concantes a list of tensors alongside the specified axis.
'''
if axis < 0:
dims = ndim(tensors[0])
if dims:
axis = axis % dims
else:
axis = 0
if py_all([is_sparse(x) for x in tensors]):
return tf.sparse_concat(axis, tensors)
else:
return tf.concat(axis, [to_dense(x) for x in tensors])
