jmduarte
commented
1 year ago hi @zahraaayii. This typically means the layers you're trying to use are too large for the way hls4ml writes the HLS.
I see your first Conv1D layer has a kernel size of 100 which is quite large.
We have improvements in larger layers in more recent versions of hls4ml (like 0.7.0rc1 that was just released), but I doubt it will work even then.
I would consider if you really need such large kernel sizes, or if they can be reduced.
zahraaayii
my model is: model = Sequential() model.add(BatchNormalization(input_shape=(1408,1))) model.add(Conv1D(3, kernel_size=(100),strides=2)) model.add(Activation("relu")) model.add(MaxPooling1D(pool_size=(2),strides=2)) model.add(Conv1D(50, (10))) model.add(MaxPooling1D(pool_size=(2),strides=2)) model.add(Activation("relu")) model.add(Conv1D(30, (30))) model.add(MaxPooling1D(pool_size=(2))) model.add(Activation("relu")) model.add(BatchNormalization()) model.add(Flatten()) model.add(Dropout(0.25)) model.add(Dense(4,activation='softmax'))
and my hls4ml configuration:
config = hls4ml.utils.config_from_keras_model(model, granularity='model')
print("-----------------------------------") print("Configuration") print_dict(config) print("-----------------------------------")
hls_model = hls4ml.converters.convert_from_keras_model(model, hls_config=config, output_dir='model_1/hls4ml_prj_2', part='xcvu9p-flgb2104-2-i', io_type='io_stream')
hls_model.build(csim=False)
error [XFORM 203-504] Stop unrolling loop
why ? help me