def test_cntk_embed():
try:
import tensorflow
has_tensorflow = True
except:
has_tensorflow = False
if has_tensorflow:
tf_baseline_embed()
else:
cntk_baseline_embed()
import cntk as C
import cntk.contrib.crosstalk.crosstalk_cntk as crct
ci = crct.instance
ci.set_workdir(workdir)
embed = C.parameter((
input_dim,
emb_dim,
))
ci.watch(embed,
'embed',
var_type=cstk.EmbedAttr,
attr=cstk.EmbedAttr(dict=dict2, input_dim=input_dim))
ci.assign('embed', load=True)
assert np.isclose(emb2, embed.value).all()
# test assign with value
ci.assign('embed', value={'a': emb1[0], 'b': emb1[1], 'c': emb1[2]})
ci.reset()
def cntk_baseline_embed():
import cntk as C
import cntk.contrib.crosstalk.crosstalk_cntk as crct
ci = crct.instance
embed = C.parameter((input_dim, emb_dim), init=emb1)
ci.watch(embed,
'embed',
var_type=cstk.EmbedAttr,
attr=cstk.EmbedAttr(dict=dict1, input_dim=input_dim))
ci.set_workdir(workdir)
ci.fetch('embed', save=True)
ci.reset()
def tf_baseline_embed():
import tensorflow as tf
import cntk.contrib.crosstalk.crosstalk_tensorflow as crtf
ci = crtf.instance
tf.reset_default_graph()
embed = tf.get_variable("embed", initializer=emb1, dtype=tf.float32)
ci.watch(embed,
'embed',
var_type=cstk.EmbedAttr,
attr=cstk.EmbedAttr(dict=dict1, input_dim=input_dim))
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
ci.set_workdir(workdir)
ci.set_data(sess, None)
ci.fetch('embed', save=True)
ci.reset()
sess.close()