Conv2d Error: No algorithm worked!

General Discussion
#1

I want to Conv2d two tensor.
However, it gives tensorflow.python.framework.errors_impl.NotFoundError: No algorithm worked! [Op:Conv2D]

Here is my code:

oneone = tf.random.uniform(shape=[1,1,10,3])
xx = tf.random.uniform([3,3,10,100])
kernel = kb.conv2d(xx, oneone, padding=‘same’)

It does work in pytorch:
torch.nn.functional.conv2d(weight_x_x_, weight_1_1_)

May I know what I missed?

#3

Yes, please have a look at Functional API document for many examples on how to build models with multiple inputs.

Please refer to the sample code below, where you will probably want to pass the image through a convolution layer, flatten the output and concatenate it with vector input:

from tensorflow.keras.layers import Input, Concatenate, Conv2D, Flatten, Dense

from tensorflow.keras.models import Model

# Define two input layers

image_input = Input((32, 32, 3))

vector_input = Input((6,))

# Convolution + Flatten for the image

conv_layer = Conv2D(32, (3,3))(image_input)

flat_layer = Flatten()(conv_layer)

# Concatenate the convolutional features and the vector input

concat_layer= Concatenate()([vector_input, flat_layer])

output = Dense(3)(concat_layer)

# define a model with a list of two inputs

model = Model(inputs=[image_input, vector_input], outputs=output)

Thank you.