I have trained LSTM network and want to do a performance comparison between
Keras and TVM on my personal laptop CPU. For that, I am using 10 values to pass
through the network directly.
data shape is [10,1,6]
######################################################################
#model is loaded from the .h5 file
data = test_X[0:10,:,:]
shape_dict = {"lstm_1_input": data.shape}
mod, params = relay.frontend.from_keras(model, shape_dict)
# compile the model
target = "llvm"
ctx = tvm.cpu(0)
with tvm.transform.PassContext(opt_level=3):
executor = relay.build_module.create_executor("graph", mod, ctx, target)
print("Test Data Shape = ",data.shape)
dtype = "float32"
data2 = data.astype(dtype)
tvm_out = executor.evaluate()(tvm.nd.array(data2), **params)
print(tvm_out)
top1_tvm = np.argmax(tvm_out.asnumpy()[0])
######################################################################
For the above code, I am getting below error
Check failed: *axis_ptr == 1 (10 vs. 1) : cannot squeeze axis with dimension
not equal to 1.
Its basically feeding the TVM multiple inputs simultaneously.
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