def call(self, inputs): if self.implementation == 1: output = K.local_conv(inputs, self.kernel, self.kernel_size, self.strides, (self.output_row, self.output_col), self.data_format) elif self.implementation == 2: output = local_conv_matmul(inputs, self.kernel, self.kernel_mask, self.compute_output_shape(inputs.shape)) elif self.implementation == 3: output = local_conv_sparse_matmul( inputs, self.kernel, self.kernel_idxs, self.kernel_shape, self.compute_output_shape(inputs.shape)) else: raise ValueError('Unrecognized implementation mode: %d.' % self.implementation) if self.use_bias: output = K.bias_add(output, self.bias, data_format=self.data_format) output = self.activation(output) return output
def call(self, inputs): output = K.local_conv(inputs, self.kernel, self.kernel_size, self.strides, (self.output_row, self.output_col), self.data_format) if self.use_bias: output = K.bias_add(output, self.bias, data_format=self.data_format) output = self.activation(output) return output
def call(self, inputs): if self.implementation == 1: output = K.local_conv(inputs, self.kernel, self.kernel_size, self.strides, (self.output_length,), self.data_format) elif self.implementation == 2: output = local_conv_matmul(inputs, self.kernel, self.kernel_mask, self.compute_output_shape(inputs.shape)) else: raise ValueError('Unrecognized implementation mode: %d.' % self.implementation) if self.use_bias: output = K.bias_add(output, self.bias, data_format=self.data_format) output = self.activation(output) return output