STT-tensorflow/tensorflow/lite/testing/op_tests/reshape.py
Nupur Garg 2fb71ff8cf Make generate_examples run in 2.0.
PiperOrigin-RevId: 298616596
Change-Id: Ib0be0a8929e75634924c28165f6fcd998b77add9
2020-03-03 08:59:39 -08:00

88 lines
3.1 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 reshape."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
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_reshape_tests(options):
"""Make a set of tests to do reshape."""
# All shapes below are suitable for tensors with 420 elements.
test_parameters = [{
"dtype": [tf.float32, tf.int32],
"input_shape": [[3, 4, 5, 7], [4, 105], [21, 5, 2, 2], [420]],
"output_shape": [[15, 28], [420], [1, -1, 5, 7], [-1]],
"constant_shape": [True, False],
"fully_quantize": [False],
}, {
"dtype": [tf.float32],
"input_shape": [[1]],
"output_shape": [[]],
"constant_shape": [True, False],
"fully_quantize": [False],
}, {
"dtype": [tf.float32],
"input_shape": [[3, 4, 5, 7], [4, 105], [21, 5, 2, 2], [420]],
"output_shape": [[15, 28], [420], [1, -1, 5, 7], [-1]],
"constant_shape": [True],
"fully_quantize": [True],
}]
def build_graph(parameters):
"""Build the graph for reshape tests."""
input_tensor = tf.compat.v1.placeholder(
dtype=parameters["dtype"],
name="input",
shape=parameters["input_shape"])
# Get shape as either a placeholder or constants.
if parameters["constant_shape"]:
output_shape = parameters["output_shape"]
input_tensors = [input_tensor]
else:
# The shape of the shape tensor.
shape_tensor_shape = [len(parameters["output_shape"])]
output_shape = tf.compat.v1.placeholder(
dtype=tf.int32, name="output_shape", shape=shape_tensor_shape)
input_tensors = [input_tensor, output_shape]
out = tf.reshape(input_tensor, shape=output_shape)
return input_tensors, [out]
def build_inputs(parameters, sess, inputs, outputs):
"""Build inputs for reshape op."""
values = [
create_tensor_data(
parameters["dtype"],
parameters["input_shape"],
min_value=-1,
max_value=1)
]
if not parameters["constant_shape"]:
values.append(np.array(parameters["output_shape"]))
return values, sess.run(outputs, feed_dict=dict(zip(inputs, values)))
make_zip_of_tests(options, test_parameters, build_graph, build_inputs)