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      1 # Copyright 2018 The TensorFlow Authors. All Rights Reserved.
      2 #
      3 # Licensed under the Apache License, Version 2.0 (the "License");
      4 # you may not use this file except in compliance with the License.
      5 # You may obtain a copy of the License at
      6 #
      7 #     http://www.apache.org/licenses/LICENSE-2.0
      8 #
      9 # Unless required by applicable law or agreed to in writing, software
     10 # distributed under the License is distributed on an "AS IS" BASIS,
     11 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
     12 # See the License for the specific language governing permissions and
     13 # limitations under the License.
     14 # ==============================================================================
     15 """Script to test TF-TRT INT8 conversion without calibration on Mnist model."""
     16 
     17 from __future__ import absolute_import
     18 from __future__ import division
     19 from __future__ import print_function
     20 
     21 import numpy as np
     22 
     23 from tensorflow.python.compiler.tensorrt.test import tf_trt_integration_test_base as trt_test
     24 from tensorflow.python.framework import constant_op
     25 from tensorflow.python.framework import dtypes
     26 from tensorflow.python.framework import ops
     27 from tensorflow.python.ops import array_ops
     28 from tensorflow.python.ops import nn
     29 from tensorflow.python.platform import test
     30 
     31 
     32 class DynamicInputShapesTest(trt_test.TfTrtIntegrationTestBase):
     33 
     34   def GetParams(self):
     35     # TODO(laigd): we should test the following cases:
     36     # - batch size is not changed, other dims are changing
     37     # - batch size is decreasing, other dims are identical
     38     # - batch size is decreasing, other dims are changing
     39     # - batch size is increasing, other dims are identical
     40     # - batch size is increasing, other dims are changing
     41     input_dims = [[[1, 5, 5, 1]], [[10, 5, 5, 1]], [[3, 5, 5, 1]],
     42                   [[1, 5, 5, 1]], [[1, 3, 1, 1]], [[2, 9, 9, 1]],
     43                   [[1, 224, 224, 1]], [[1, 128, 224, 1]]]
     44     expected_output_dims = input_dims
     45 
     46     g = ops.Graph()
     47     with g.as_default():
     48       x = array_ops.placeholder(
     49           shape=(None, None, None, 1), dtype=dtypes.float32, name="input")
     50       conv_filter1 = constant_op.constant(
     51           np.ones([3, 3, 1, 8]), name="weights1", dtype=dtypes.float32)
     52       bias1 = constant_op.constant(np.random.randn(8), dtype=dtypes.float32)
     53       x = nn.conv2d(
     54           input=x,
     55           filter=conv_filter1,
     56           strides=[1, 1, 1, 1],
     57           padding="SAME",
     58           name="conv")
     59       x = nn.bias_add(x, bias1)
     60       x = nn.relu(x)
     61       conv_filter2 = constant_op.constant(
     62           np.ones([3, 3, 8, 1]), name="weights2", dtype=dtypes.float32)
     63       bias2 = constant_op.constant(np.random.randn(1), dtype=dtypes.float32)
     64       x = nn.conv2d(
     65           input=x,
     66           filter=conv_filter2,
     67           strides=[1, 1, 1, 1],
     68           padding="SAME",
     69           name="conv")
     70       x = nn.bias_add(x, bias2)
     71       x = array_ops.identity(x, name="output")
     72 
     73     return trt_test.TfTrtIntegrationTestParams(
     74         gdef=g.as_graph_def(),
     75         input_names=["input"],
     76         input_dims=input_dims,
     77         output_names=["output"],
     78         expected_output_dims=expected_output_dims)
     79 
     80   def GetConversionParams(self, run_params):
     81     """Return a ConversionParams for test."""
     82     conversion_params = super(DynamicInputShapesTest,
     83                               self).GetConversionParams(run_params)
     84     return conversion_params._replace(
     85         maximum_cached_engines=10,
     86         # Disable layout optimizer, since it will convert BiasAdd with NHWC
     87         # format to NCHW format under four dimentional input.
     88         rewriter_config=trt_test.OptimizerDisabledRewriterConfig())
     89 
     90   def ExpectedEnginesToBuild(self, run_params):
     91     return ["TRTEngineOp_0"]
     92 
     93   def ShouldRunTest(self, run_params):
     94     return (run_params.dynamic_engine and
     95             not trt_test.IsQuantizationMode(run_params.precision_mode))
     96 
     97   def ExpectedAbsoluteTolerance(self, run_params):
     98     """The absolute tolerance to compare floating point results."""
     99     return 1.e-03 if run_params.precision_mode == "FP32" else 1.e-01
    100 
    101   def ExpectedRelativeTolerance(self, run_params):
    102     """The relative tolerance to compare floating point results."""
    103     return 1.e-03 if run_params.precision_mode == "FP32" else 1.e-01
    104 
    105 
    106 if __name__ == "__main__":
    107   test.main()
    108