diff --git a/x2paddle/op_mapper/caffe_op_mapper.py b/x2paddle/op_mapper/caffe_op_mapper.py index 5d29c3ef66203421482b4978f1fdb51dfc840f6d..087c55a6d9a26cfa0d6f72e045edde3f81ee9d6b 100644 --- a/x2paddle/op_mapper/caffe_op_mapper.py +++ b/x2paddle/op_mapper/caffe_op_mapper.py @@ -229,8 +229,8 @@ class CaffeOpMapper(OpMapper): node.layer_name, node.layer_type)) input_c = node.input_shape[0][1] output_c = channel - data.append(np.zeros([output_c, input_c, kernel[0], kernel[1]])) - data.append(np.zeros([output_c,])) + data.append(np.zeros([output_c, input_c, kernel[0], kernel[1]]).astype('float32')) + data.append(np.zeros([output_c,])).astype('float32') else: data = self.adjust_parameters(node) self.weights[node.layer_name + '_weights'] = data[0] @@ -276,8 +276,8 @@ class CaffeOpMapper(OpMapper): node.layer_name, node.layer_type)) input_c = node.input_shape[0][1] output_c = channel - data.append(np.zeros([output_c, input_c, kernel[0], kernel[1]])) - data.append(np.zeros([output_c,])) + data.append(np.zeros([output_c, input_c, kernel[0], kernel[1]]).astype('float32')) + data.append(np.zeros([output_c,]).astype('float32')) else: data = self.adjust_parameters(node) self.weights[node.layer_name + '_weights'] = data[0] @@ -374,8 +374,8 @@ class CaffeOpMapper(OpMapper): input_c = node.input_shape[0][1] output_c = params.num_output data = [] - data.append(np.zeros([input_c, output_c])) - data.append(np.zeros([output_c])) + data.append(np.zeros([input_c, output_c]).astype('float32').astype('float32')) + data.append(np.zeros([output_c]).astype('float32').astype('float32')) else: data = self.adjust_parameters(node) # Reshape the parameters to Paddle's ordering @@ -627,8 +627,8 @@ class CaffeOpMapper(OpMapper): print('The parameter of {} (type is {}) is not set. So we set the parameters as 0'.format( node.layer_name, node.layer_type)) input_c = node.input_shape[0][1] - mean = np.zeros([input_c,]) - variance = np.zeros([input_c,]) + mean = np.zeros([input_c,]).astype('float32') + variance = np.zeros([input_c,]).astype('float32') scale = 0 else: node.data = [np.squeeze(i) for i in node.data] @@ -658,8 +658,8 @@ class CaffeOpMapper(OpMapper): print('The parameter of {} (type is {}) is not set. So we set the parameters as 0'.format( node.layer_name, node.layer_type)) input_c = node.input_shape[0][1] - self.weights[node.layer_name + '_scale'] = np.zeros([input_c,]) - self.weights[node.layer_name + '_offset'] = np.zeros([input_c,]) + self.weights[node.layer_name + '_scale'] = np.zeros([input_c,]).astype('float32') + self.weights[node.layer_name + '_offset'] = np.zeros([input_c,]).astype('float32') else: self.weights[node.layer_name + '_scale'] = np.squeeze(node.data[0]) self.weights[node.layer_name + '_offset'] = np.squeeze(node.data[1])