Fix missing defines in compilation flags that caused missing ops and add a simple test to validate functionality

tensorflow/contrib/tensorrt/BUILD

@@ -52,8 +52,6 @@ tf_custom_op_library(
         ":trt_engine_op_kernel",
         ":trt_shape_function",
         "//tensorflow/core:lib_proto_parsing",
-        "//tensorflow/core/kernels:bounds_check_lib",
-        "//tensorflow/core/kernels:ops_util_hdrs",
         "@local_config_tensorrt//:nv_infer",
     ],
 )
@@ -77,8 +75,10 @@ cc_library(
     name = "trt_engine_op_kernel",
     srcs = ["kernels/trt_engine_op.cc"],
     hdrs = ["kernels/trt_engine_op.h"],
+    copts = tf_copts(),
     deps = [
         ":trt_logging",
+        "//tensorflow/core:stream_executor_headers_lib",
         "//tensorflow/core:framework_headers_lib",
         "//tensorflow/core:gpu_headers_lib",
         "//tensorflow/core:lib_proto_parsing",
@@ -212,9 +212,6 @@ cc_library(
     linkstatic = 1,
     deps = [
         "//tensorflow/core:graph",
-        # "//tensorflow/core:core_cpu",
-        # "//tensorflow/core:lib_proto_parsing",
-        # "//third_party/eigen3",
         "@protobuf_archive//:protobuf_headers",
     ],
 )

tensorflow/contrib/tensorrt/kernels/trt_engine_op.cc

@@ -19,6 +19,8 @@ limitations under the License.
 #include "cuda/include/cuda_runtime_api.h"
 #include "tensorflow/contrib/tensorrt/log/trt_logger.h"
 #include "tensorflow/core/platform/logging.h"
+//#include "tensorflow/core/framework/device_base.h"
+#include "tensorflow/core/platform/stream_executor.h"
 
 namespace tensorflow {
 namespace tensorrt {

tensorflow/contrib/tensorrt/test/test_tftrt.py

@@ -0,0 +1,53 @@
+#  Script to test TF-TensorRT integration
+#
+#
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+import tensorflow as tf
+import tensorflow.contrib.tensorrt as trt
+import numpy as np
+
+def getSimpleGraphDef():
+    ''' 
+    Create a simple graph and return its graph_def
+    '''
+    g=tf.Graph()
+    with g.as_default():
+        A=tf.placeholder(dtype=tf.float32,shape=(None,24,24,2),name="input")
+        e=tf.constant([ [[[ 1., 0.5, 4., 6., 0.5, 1. ],
+                        [ 1., 0.5, 1., 1., 0.5, 1. ]]] ],
+                      name="weights",dtype=tf.float32)
+        conv=tf.nn.conv2d(input=A,filter=e,strides=[1,2,2,1],padding="SAME",name="conv")
+        b=tf.constant([  4., 1.5, 2., 3., 5., 7. ],
+                      name="bias",dtype=tf.float32)
+        t=tf.nn.bias_add(conv,b,name="biasAdd")
+        relu=tf.nn.relu(t,"relu")
+        idty=tf.identity(relu,"ID")
+        v=tf.nn.max_pool(idty,[1,2,2,1],[1,2,2,1],"VALID",name="max_pool")
+        out = tf.squeeze(v,name="output")
+    return g.as_graph_def()
+
+def runGraph(gdef,dumm_inp):
+    gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=0.50)
+    tf.reset_default_graph()
+    g=tf.Graph()
+    with g.as_default():
+        inp,out=tf.import_graph_def(graph_def=gdef,
+                            return_elements=["input","output"])
+        inp=inp.outputs[0]
+        out=out.outputs[0]
+    with tf.Session(config=tf.ConfigProto(gpu_options=gpu_options),
+                    graph=g) as sess:
+        val=sess.run(out,{inp:dumm_inp})
+    return val
+if "__main__" in  __name__:
+    inpDims=(100,24,24,2)
+    dummy_input=np.random.random_sample(inpDims)
+    gdef=getSimpleGraphDef() #get graphdef
+    trt_graph=trt.CreateInferenceGraph(gdef,["output"],inpDims[0]) # get optimized graph
+    o1=runGraph(gdef,dummy_input)
+    o2=runGraph(trt_graph,dummy_input)
+    assert(np.array_equal(o1,o2))
+