def testSplitDictOfTensorsAssert(self):
t1 = tf.constant([[1], [7], [8]])
t2 = tf.constant([[5], [9], [10]])
t3 = tf.constant([[13], [14]])
tensor_dict = {'a': t1, 'b': t2, 'c': t3}
num_splits = 2
with self.assertRaisesRegexp(
ValueError,
'can\'t split axis of size 2 into pieces of size \[2,1\]'):
splits = input_generator_helper.SplitDictOfTensors(
tensor_dict, num_splits)
def testDecoderFPropSplitBatch(self, dtype=tf.float32):
with self.session(use_gpu=True) as sess:
tf.set_random_seed(_TF_RANDOM_SEED)
p = self._DecoderParams(dtype=dtype)
dec = decoder.TransformerDecoder(p)
src_enc, src_paddings, targets = self._Inputs(dtype=dtype)
src_enc1, src_enc2 = tf.split(src_enc, 2, 1)
src_paddings1, src_paddings2 = tf.split(src_paddings, 2, 1)
# source idx <-> target idx:
# 0 <-> (0, 4), 1 <-> (1, 5), 2 <-> (2, 6), 3 <-> (3, 7)
tgts = ig_helper.SplitDictOfTensors(targets, 4)
targets1 = py_utils.NestedMap({
'ids':
tf.concat([tgts[0]['ids'], tgts[2]['ids']], 0),
'labels':
tf.concat([tgts[0]['labels'], tgts[2]['labels']], 0),
'weights':
tf.concat([tgts[0]['weights'], tgts[2]['weights']], 0),
'paddings':
tf.concat([tgts[0]['paddings'], tgts[2]['paddings']], 0)
})
targets2 = py_utils.NestedMap({
'ids':
tf.concat([tgts[1]['ids'], tgts[3]['ids']], 0),
'labels':
tf.concat([tgts[1]['labels'], tgts[3]['labels']], 0),
'weights':
tf.concat([tgts[1]['weights'], tgts[3]['weights']], 0),
'paddings':
tf.concat([tgts[1]['paddings'], tgts[3]['paddings']], 0)
})
loss, _ = dec.FPropDefaultTheta(src_enc, src_paddings, targets,
None)['loss']
loss1, _ = dec.FPropDefaultTheta(src_enc1, src_paddings1, targets1,
None)['loss']
loss2, _ = dec.FPropDefaultTheta(src_enc2, src_paddings2, targets2,
None)['loss']
tf.global_variables_initializer().run()
actual_loss, actual_loss1, actual_loss2 = sess.run(
[loss, loss1, loss2])
print('actual loss = ', actual_loss)
print('actual loss1 = ', actual_loss1)
print('actual loss2 = ', actual_loss2)
self.assertAlmostEqual(actual_loss,
np.mean([actual_loss1, actual_loss2]),
delta=0.0001)
def testSplitDictOfTensorsUneven(self):
with self.session(use_gpu=False) as sess:
t1 = tf.constant([[1], [4], [8]])
t2 = tf.constant([[5], [9], [10]])
t3 = tf.constant([[13], [14], [11]])
tensor_dict = {'a': t1, 'b': t2, 'c': t3}
num_splits = 2
splits = input_generator_helper.SplitDictOfTensors(
tensor_dict, num_splits)
expected = [{
'a': np.array([[1], [4]]),
'b': np.array([[5], [9]]),
'c': np.array([[13], [14]])
}, {
'a': np.array([[8]]),
'b': np.array([[10]]),
'c': np.array([[11]])
}]
actual = sess.run(splits)
self._assertListOfDictsEqual(actual, expected)