tensorflow

问题 After running my model for one epoch it crashed with following error message: InvalidArgumentError: Specified a list with shape [60,9] from a tensor with shape [56,9] [[{{node TensorArrayUnstack/TensorListFromTensor}}]] [[sequential_7/lstm_17/PartitionedCall]] [Op:__inference_train_function_29986] This happened after I changed the LSTM Layer to stateful=True and had to pass the batch_input_shape Argument instead of the input_shape Below is my code, I'm sure it has something to do with the

问题 I am trying to wrap my head around ML and AI using TensorFlow. There is an example problem on the website which discusses the processing of .CSV data. The .CVS data is said to have been taken from the titanic and essentially contains categorical and numerical features that will be used to label a passenger as dead or alive. First of all, if anyone know or has any resources or references that discusses that example in more detail than is done on the TensorFlow website, please could you kindly

问题 I am using keras applications for transfer learning with resnet 50 and inception v3 but when predicting always get [[ 0.]] The below code is for a binary classification problem. I have also tried vgg19 and vgg16 but they work fine, its just resnet and inception. The dataset is a 50/50 split. And I am only changing the model = applications.resnet50.ResNet50 line of code for each model. below is the code: from keras.callbacks import EarlyStopping early_stopping = EarlyStopping(monitor='val_loss

问题 I am using keras applications for transfer learning with resnet 50 and inception v3 but when predicting always get [[ 0.]] The below code is for a binary classification problem. I have also tried vgg19 and vgg16 but they work fine, its just resnet and inception. The dataset is a 50/50 split. And I am only changing the model = applications.resnet50.ResNet50 line of code for each model. below is the code: from keras.callbacks import EarlyStopping early_stopping = EarlyStopping(monitor='val_loss

问题 I'm trying to warp a frame from view1 to view2 using ground truth depth map, pose information, and camera matrix. I've been able to remove most of the for-loops and vectorize it, except one for-loop. When warping, multiple pixels in view1 may get mapped to a single location in view2, due to occlusions. In this case, I need to pick the pixel with the lowest depth value (foreground object). I'm not able to vectorize this part of the code. Any help to vectorize this for loop is appreciated.

问题 I am a newbie research Deeplearning. I load a saved model with tensorflow and made a API with flask but I get error 'Container localhost does not exist.' when I predict, please help me fix it. Thank you. tensorflow version 1.13.1 keras version 2.2.4 flask version 1.0.3 I run it by command 'python app.py' This is my code: from flask import Flask, request from tensorflow.python.keras.models import load_model import numpy as np import tensorflow as tf from tensorflow.python.keras.applications

问题 Im doing a neural network encoding every variable and when im going to fit the model, an error raises. indices[201] = [0,8] is out of order. Many sparse ops require sorted indices. Use `tf.sparse.reorder` to create a correctly ordered copy. [Op:SerializeManySparse] I dunno how to solve it. I can print some code here and if u want more i can still printing it def process_atributes(df, train, test): continuas = ['Trip_Duration'] cs = MinMaxScaler() trainCont = cs.fit_transform(train[continuas])

问题 Im doing a neural network encoding every variable and when im going to fit the model, an error raises. indices[201] = [0,8] is out of order. Many sparse ops require sorted indices. Use `tf.sparse.reorder` to create a correctly ordered copy. [Op:SerializeManySparse] I dunno how to solve it. I can print some code here and if u want more i can still printing it def process_atributes(df, train, test): continuas = ['Trip_Duration'] cs = MinMaxScaler() trainCont = cs.fit_transform(train[continuas])

问题 I want to implement scatter and gather operations of Tensorflow or PyTorch in Numpy. I have been scratching my head for a while. Any pointers are greatly appreciated! PyTorch Scatter PyTorch Gather 回答1: The scatter method turned out to be way more work than I anticipated. I did not find any ready made function in NumPy for it. I'm sharing it here in the interest of anyone who may need to implement it with NumPy. (p.s. self is the destination or output of the method.) def scatter_numpy(self,

问题 I want to implement scatter and gather operations of Tensorflow or PyTorch in Numpy. I have been scratching my head for a while. Any pointers are greatly appreciated! PyTorch Scatter PyTorch Gather 回答1: The scatter method turned out to be way more work than I anticipated. I did not find any ready made function in NumPy for it. I'm sharing it here in the interest of anyone who may need to implement it with NumPy. (p.s. self is the destination or output of the method.) def scatter_numpy(self,