def run_test_case(self, dataset, truth_data, batch_size=None):
"""run_test_case"""
iterator = data.make_one_shot_iterator(dataset)
next_element = iterator.get_next()
def is_float(dtype):
return dtype in [dtypes.float16, dtypes.float32, dtypes.float64]
batch_counter = batch_size
with self.test_session() as sess:
for row in range(len(truth_data.data[0])):
if batch_size is None:
value = sess.run(next_element)
else:
if batch_counter == batch_size:
value_batch = sess.run(next_element)
print(value_batch)
batch_counter = 0
value = [v[batch_counter] for v in value_batch]
batch_counter += 1
for i, col in enumerate(dataset.columns):
if truth_data.output_shapes[col].ndims == 0:
if is_float(truth_data.output_types[col]):
self.assertAlmostEqual(value[i], truth_data.data[col][row], 4)
else:
self.assertEqual(value[i], truth_data.data[col][row])
elif truth_data.output_shapes[col].ndims == 1:
if is_float(truth_data.output_types[col]):
for j, v in enumerate(value[i]):
self.assertAlmostEqual(v, truth_data.data[col][row][j], 4)
else:
self.assertListEqual(value[i].tolist(), truth_data.data[col][row])
def run_test_case(self, dataset, truth_data):
"""run_test_case"""
iterator = data.make_one_shot_iterator(dataset)
next_element = iterator.get_next()
def is_float(dtype):
return dtype in [dtypes.float16, dtypes.float32, dtypes.float64]
with self.test_session() as sess:
for row in range(len(truth_data.data[0])):
value = sess.run(next_element)
for i, col in enumerate(dataset.columns):
if truth_data.output_shapes[col].ndims == 0:
if is_float(truth_data.output_types[col]):
self.assertAlmostEqual(value[i],
truth_data.data[col][row],
4)
else:
self.assertEqual(value[i],
truth_data.data[col][row])
elif truth_data.output_shapes[col].ndims == 1:
if is_float(truth_data.output_types[col]):
for j, v in enumerate(value[i]):
self.assertAlmostEqual(
v, truth_data.data[col][row][j], 4)
else:
self.assertListEqual(value[i].tolist(),
truth_data.data[col][row])
def pipeline(*args):
# TF2 replacement for: iterator = dataset.make_one_shot_iterator()
iterator = compat_v1_data.make_one_shot_iterator(dataset)
next_example, next_label = iterator.get_next()
outputs = functional_ops._convert_to_list(args) # pylint: disable=W0212
outputs.append(next_example)
outputs.append(next_label)
for stage in stages:
outputs = stage(
*functional_ops._convert_to_list(outputs)) # pylint: disable=W0212
return outputs
def testBufferDataset(self):
dataset = tu.create_single_increasing_dataset(10, shape=[4, 4])
dataset = dataset.take(3)
dataset = ipu.data.ops.dataset_ops.BufferDataset(dataset, 2)
itr = compat_v1_data.make_one_shot_iterator(dataset)
next_data = itr.get_next()
with self.session() as sess:
self.assertAllEqual(sess.run(next_data)[0], np.zeros([4, 4]))
self.assertAllEqual(sess.run(next_data)[0], np.ones([4, 4]))
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(sess.run(next_data))