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The shape of my train data normal_scale is (398,10,3),I try the following code, but it turns a shape error.
normal_scale
(398,10,3)
import seq2seq from seq2seq.models import Seq2Seq model = Seq2Seq(batch_input_shape=(16, 10, 3), hidden_dim=10, output_length=10, output_dim=3, depth=4) model.compile(loss='mse', optimizer='rmsprop') model.summary() model.fit(x=normal_scale,y=normal_scale)
My model is
_________________________________________________________________________________________________ Layer (type) Output Shape Param # Connected to ================================================================================================== input_1231 (InputLayer) (16, 10, 3) 0 __________________________________________________________________________________________________ time_distributed_19 (TimeDistri (16, 10, 10) 40 input_1231[0][0] __________________________________________________________________________________________________ private__optional_input_place_h (2,) 0 __________________________________________________________________________________________________ private__optional_input_place_h (2,) 0 __________________________________________________________________________________________________ private__optional_input_place_h (2,) 0 __________________________________________________________________________________________________ recurrent_sequential_37 (Recurr [(16, 10), (16, 10), 3360 time_distributed_19[0][0] private__optional_input_place_hol private__optional_input_place_hol private__optional_input_place_hol __________________________________________________________________________________________________ dense_856 (Dense) (16, 3) 33 recurrent_sequential_37[0][0] __________________________________________________________________________________________________ recurrent_sequential_38 (Recurr (16, 10, 3) 2372 dense_856[0][0] recurrent_sequential_37[0][1] recurrent_sequential_37[0][2] dense_856[0][0] ================================================================================================== Total params: 5,805 Trainable params: 5,805 Non-trainable params: 0
Actually I don't have data shape of (32, 10, 3) , the error is
ValueError: Cannot feed value of shape (32, 10, 3) for Tensor u'input_1231:0', which has shape '(16, 10, 3)'
The text was updated successfully, but these errors were encountered:
Actually I find the sample of data must be the whole-number multiple of the batch_size,and you need to set the batch_size at the model.fit
batch_size
model.fit
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The shape of my train data
normal_scale
is(398,10,3)
,I try the following code, but it turns a shape error.My model is
Actually I don't have data shape of (32, 10, 3) , the error is
ValueError: Cannot feed value of shape (32, 10, 3) for Tensor u'input_1231:0', which has shape '(16, 10, 3)'
The text was updated successfully, but these errors were encountered: