1D has 2D kernels about keras-resnet HOT 10 OPEN

same error here

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Yeah, it also confuse me a lot.

from keras-resnet.

Same error.

In keras_resnet/models/_id.py

x = keras.layers.Conv1D(64, (7, 7), strides=(2, 2), use_bias=False, name="conv1")(x)
and
x = keras.layers.MaxPooling1D((3, 3), strides=(2, 2), padding="same", name="pool1")(x)

should be:

x = keras.layers.Conv1D(64, 7, strides=2, use_bias=False, name="conv1")(x)
and
x = keras.layers.MaxPooling1D(3, strides=2, padding="same", name="pool1")(x)

from keras-resnet.

I have proposed a fix by uploading the code I have modified to work with 1D time series.

from keras-resnet.

so, this is the issue.

from keras-resnet.

I have a dataset with 1600 rows and 103 columns, when I used Conv1D in a sequential model I reshaped my data to (1600,103,1) and put the input_shape=(103,1) it worked fine. But when I use this model, after adding the fix in regards to kernel and strides, and shape (103,1) I get this error:
ValueError: Input 0 of layer conv1 is incompatible with the layer: : expected min_ndim=4, found ndim=3. Full shape received: (None, 103, 1)

@tackoo

from keras-resnet.

@tackoo there is still the dimension problem after the fixes

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from keras-resnet.

Is it possible to install this fork?

from keras-resnet.

from keras-resnet.