tflite_model_buf = f.read()
data = np.random.uniform(size=(1, 300, 300, 3)).astype('float32')
tflite_output = run_tflite_graph(tflite_model_buf, data)
- tvm_output = run_tvm_graph(tflite_model_buf, data, 'normalized_input_image_tensor')
- tvm.testing.assert_allclose(np.squeeze(tvm_output[0]), np.squeeze(tflite_output[0]),
- rtol=1e-5, atol=1e-5)
+ tvm_output = run_tvm_graph(tflite_model_buf, data, 'normalized_input_image_tensor', num_output=2)
+ for i in range(2):
+ tvm.testing.assert_allclose(np.squeeze(tvm_output[i]), np.squeeze(tflite_output[i]),
+ rtol=1e-5, atol=2e-5)
#######################################################################
# MediaPipe