[NNVM][TENSORFLOW]Fix lstm testcase to support get_output without size input (#1731)

* [NNVM][TENSORFLOW]Fix lstm testcase issue to support get_output without size input

* removed redundant

* Enabled inceptionV1 testcase

nnvm/tests/python/frontend/tensorflow/test_forward.py

@@ -26,7 +26,7 @@ import nnvm.testing.tf
 #######################################################################
 # Generic run functions for TVM & tensorflow
 # ------------------------------------------
-def run_tvm_graph(graph_def, input_data, input_node, output_shape, output_dtype, target='llvm'):
+def run_tvm_graph(graph_def, input_data, input_node, num_output=1, target='llvm'):
     """ Generic function to compile on nnvm and execute on tvm """
 
     layout = None
@@ -62,10 +62,10 @@ def run_tvm_graph(graph_def, input_data, input_node, output_shape, output_dtype,
     # execute
     m.run()
     # get outputs
-    if isinstance(output_shape, list) and isinstance(output_dtype, list):
+    if num_output > 1:
         tvm_output_list = []
-        for i, s in enumerate(output_shape):
-            tvm_output = m.get_output(i, tvm.nd.empty((s), output_dtype[i]))
+        for i in range(0, num_output):
+            tvm_output = m.get_output(i)
             tvm_output_list.append(tvm_output.asnumpy())
         return tvm_output_list
     else:
@@ -119,8 +119,7 @@ def compare_tf_with_tvm(in_data, in_name, out_name, init_global_variables=False,
             if no_gpu and device == 'cuda':
                 continue
 
-            tvm_output = run_tvm_graph(final_graph_def, in_data,
-                                       in_node, tf_output.shape, tf_output.dtype, target=device)
+            tvm_output = run_tvm_graph(final_graph_def, in_data, in_node, target=device)
             np.testing.assert_allclose(tf_output, tvm_output, atol=1e-5, rtol=1e-5)
 
         sess.close()
@@ -572,14 +571,12 @@ def _test_lstm_cell(batch_size, num_hidden, num_layers, forget_bias, dtype):
     graph_def, tf_out = _get_tensorflow_output()
     tvm_output = run_tvm_graph(graph_def, [input_data, in_state_c, in_state_h],
                                ['root/Placeholder', 'root/lstm_cell/LSTMBlockCell_c',
-                                'root/lstm_cell/LSTMBlockCell_h'],
-                               [tf_out[0].shape, (2, batch_size, num_hidden)],
-                               [tf_out[0].dtype, tf_out[1].dtype])
+                                'root/lstm_cell/LSTMBlockCell_h'], num_output=2)
     assert isinstance(tvm_output, list)
 
     out = tvm_output[0]
     out_state = tvm_output[1]
-    out_state_tup = np.split(out_state, indices_or_sections=2, axis=0)
+    out_state_tup = np.split(out_state, indices_or_sections=2, axis=1)
     out_state_c = np.reshape(out_state_tup[0], (batch_size, num_hidden))
     out_state_h = np.reshape(out_state_tup[1], (batch_size, num_hidden))
     tvm_out = [out, out_state_c, out_state_h]
@@ -587,7 +584,6 @@ def _test_lstm_cell(batch_size, num_hidden, num_layers, forget_bias, dtype):
 
 def test_forward_lstm():
     '''test LSTM block cell'''
-    return
     _test_lstm_cell(1, 2, 1, 0.0, 'float32')
 
 
@@ -656,7 +652,7 @@ def test_forward_inception_v3():
 
         with tf.Session() as sess:
             tf_output = run_tf_graph(sess, data, 'input:0', 'InceptionV3/Predictions/Reshape_1:0')
-            tvm_output = run_tvm_graph(graph_def, data, 'input', tf_output.shape, 'float32')
+            tvm_output = run_tvm_graph(graph_def, data, 'input')
             np.testing.assert_allclose(tf_output, tvm_output, rtol=1e-5, atol=1e-5)
 
 #######################################################################
@@ -692,7 +688,7 @@ def test_forward_inception_v1():
 
         with tf.Session() as sess:
             tf_output = run_tf_graph(sess, data, 'DecodeJpeg/contents:0', 'softmax:0')
-            tvm_output = run_tvm_graph(graph_def, tvm_data, 'DecodeJpeg/contents', tf_output.shape, 'float32')
+            tvm_output = run_tvm_graph(graph_def, tvm_data, 'DecodeJpeg/contents')
             np.testing.assert_allclose(tf_output, tvm_output, rtol=1e-5, atol=1e-5)
 
 #######################################################################
@@ -710,7 +706,7 @@ def test_forward_mobilenet():
 
         with tf.Session() as sess:
             tf_output = run_tf_graph(sess, data, 'input:0', out_node + ':0')
-            tvm_output = run_tvm_graph(graph_def, data, 'input', tf_output.shape, 'float32')
+            tvm_output = run_tvm_graph(graph_def, data, 'input')
             np.testing.assert_allclose(np.squeeze(tvm_output), np.squeeze(tf_output), rtol=1e-5, atol=1e-5)
 
 #######################################################################
@@ -1029,7 +1025,7 @@ if __name__ == '__main__':
     test_forward_ptb()
 
     # RNN
-    #test_forward_lstm()
+    test_forward_lstm()
 
     # Elementwise
     test_forward_ceil()