STT-tensorflow/tensorflow/lite/testing/op_tests/concat.py
TensorFlower Gardener 3adc7cf2c9 Merge pull request from wwwind:op_tests_16x8
PiperOrigin-RevId: 320661178
2020-07-10 13:14:01 -07:00

103 lines
3.3 KiB
Python

# Copyright 2019 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Test configs for concat."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow.compat.v1 as tf
from tensorflow.lite.testing.zip_test_utils import create_tensor_data
from tensorflow.lite.testing.zip_test_utils import make_zip_of_tests
from tensorflow.lite.testing.zip_test_utils import register_make_test_function
@register_make_test_function()
def make_concat_tests(options):
"""Make a set of tests to do concatenation."""
test_parameters = [{
"base_shape": [[1, 3, 4, 3], [3, 4]],
"num_tensors": [1, 2, 3, 4, 5, 6],
"axis": [0, 1, 2, 3, -3, -2, -1],
"type": [tf.float32, tf.uint8, tf.int32, tf.int64],
"fully_quantize": [False],
"quant_16x8": [False],
"dynamic_range_quantize": [False],
}, {
"base_shape": [[1, 3, 4, 3], [3, 4], [2, 3, 4, 3]],
"num_tensors": [1, 2, 3, 4, 5, 6],
"axis": [1, 2, 3, -3, -2, -1],
"type": [tf.float32],
"fully_quantize": [True],
"quant_16x8": [False],
"dynamic_range_quantize": [False],
}, {
"base_shape": [[1, 3, 4, 3]],
"num_tensors": [6],
"axis": [-1],
"type": [tf.float32],
"fully_quantize": [True],
"quant_16x8": [True],
"dynamic_range_quantize": [False],
}, {
"base_shape": [[1, 3, 4, 3]],
"num_tensors": [6],
"axis": [1],
"type": [tf.float32],
"fully_quantize": [False],
"quant_16x8": [False],
"dynamic_range_quantize": [True],
}]
def get_shape(parameters, delta):
"""Return a tweaked version of 'base_shape'."""
axis = parameters["axis"]
shape = parameters["base_shape"][:]
if axis < 0:
axis += len(shape)
if axis < len(shape):
shape[axis] += delta
return shape
def build_graph(parameters):
all_tensors = []
for n in range(0, parameters["num_tensors"]):
input_tensor = tf.compat.v1.placeholder(
dtype=parameters["type"],
name=("input%d" % n),
shape=get_shape(parameters, n))
all_tensors.append(input_tensor)
out = tf.concat(all_tensors, parameters["axis"])
return all_tensors, [out]
def build_inputs(parameters, sess, inputs, outputs):
all_values = []
for n in range(0, parameters["num_tensors"]):
input_values = create_tensor_data(
parameters["type"],
get_shape(parameters, n),
min_value=-1,
max_value=1)
all_values.append(input_values)
return all_values, sess.run(
outputs, feed_dict=dict(zip(inputs, all_values)))
make_zip_of_tests(
options,
test_parameters,
build_graph,
build_inputs,
expected_tf_failures=75)