def make_placeholder(x, sym_input_dict, gear):
"""define a tensorflow placeholder for xdl input x.
Args:
x: xdl embedding info returned by xdl.embedding()
Returns:
a tf placeholder
Raises:
None
"""
import xdl.python.sparse_engine.embedding as emb
if x.shape is None or len(x.shape) == 0:
raise Exception("no shape info")
emb_info = emb.get_embedding_info(x)
if emb_info is not None:
emb_info._output_tensor = x
name = create_name(emb_info.name)
add_var_mapping(emb_info.var, name)
sym_input_dict[name] = x
return mx.sym.Variable(name,
shape=[x.shape[0], emb_info.emb_dim],
dtype='float32',
__create_by_xdl__=True)
else:
global _GEAR_INPUTS
name = create_name("input")
if gear:
name += '_gear'
_GEAR_INPUTS.append(name)
import xdl.python.backend.mxnet.convert_utils as cu
sym_input_dict[name] = x
return mx.sym.Variable(name,
shape=x.shape,
dtype=cu.XDL2MX.convert_type(x.dtype),
__create_by_xdl__=True)
def make_placeholder(x):
"""define a tensorflow placeholder for xdl input x.
Args:
x: a xdl dense or embedding tensor
Returns:
a tf placeholder
Raises:
None
"""
emb_info = get_embedding_info(x)
if emb_info is not None:
if emb_info.combiner != 'tile':
placeholder = tf.placeholder(tf.float32,
name=emb_info.name,
shape=[None, emb_info.emb_dim])
else:
placeholder = tf.placeholder(tf.float32,
name=emb_info.name,
shape=[None, emb_info.tile_length])
emb_info._output_tensor = x
add_var_mapping(emb_info.var, placeholder.name)
add_to_collection(BACKPROP_VARS, (placeholder.name, placeholder))
return placeholder
else:
if x.shape is None:
shape = None
elif len(x.shape) == 0:
shape = x.shape
else:
shape = [None]
if len(x.shape) > 1:
shape.extend(x.shape[1:])
return tf.placeholder(XDL2TF.convert_type(x.dtype), shape=shape)
def make_placeholder(x):
"""define a tensorflow placeholder for xdl input x.
Args:
x: a xdl dense or embedding tensor
Returns:
a tf placeholder
Raises:
None
"""
emb_info = get_embedding_info(x)
if emb_info is not None:
placeholder = tf.placeholder(
tf.float32,
name=emb_info.name,
shape=[None, emb_info.emb_dim])
emb_info._output_tensor = x
add_var_mapping(emb_info.var, placeholder.name)
add_to_collection(BACKPROP_VARS, (placeholder.name, placeholder))
return placeholder
else:
return tf.placeholder(XDL2TF.convert_type(x.dtype), shape=x.shape)