tensorflow

Tensorflow (.pb) format to Keras (.h5)

由 China☆狼群 提交于 2020-12-25 18:47:12
问题 I am trying to convert my model in Tensorflow (.pb) format to Keras (.h5) format to view post hoc attention visualisation. I have tried below code. file_pb = "/test.pb" file_h5 = "/test.h5" loaded_model = tf.keras.models.load_model(file_pb) tf.keras.models.save_keras_model(loaded_model, file_h5) loaded_model_from_h5 = tf.keras.models.load_model(file_h5) Can anyone help me with this? Is this even possible? 回答1: In the Latest Tensorflow Version (2.2) , when we Save the Model using tf.keras

Tensorflow (.pb) format to Keras (.h5)

由 ﹥＞﹥吖頭↗ 提交于 2020-12-25 18:47:09
问题 I am trying to convert my model in Tensorflow (.pb) format to Keras (.h5) format to view post hoc attention visualisation. I have tried below code. file_pb = "/test.pb" file_h5 = "/test.h5" loaded_model = tf.keras.models.load_model(file_pb) tf.keras.models.save_keras_model(loaded_model, file_h5) loaded_model_from_h5 = tf.keras.models.load_model(file_h5) Can anyone help me with this? Is this even possible? 回答1: In the Latest Tensorflow Version (2.2) , when we Save the Model using tf.keras

tensorflow:Your input ran out of data

由 二次信任 提交于 2020-12-25 09:35:14
问题 I am working on a seq2seq keras/tensorflow 2.0 model. Every time the user inputs something, my model prints the response perfectly fine. However on the last line of each response I get this: You: WARNING:tensorflow:Your input ran out of data; interrupting training. Make sure that your dataset or generator can generate at least steps_per_epoch * epochs batches (in this case, 2 batches). You may need to use the repeat() function when building your dataset. The "You:" is my last output, before

程序员带娃有多“恐怖” ？！

由 ≯℡__Kan透↙ 提交于 2020-12-25 09:14:41
Python实战社群 Java实战社群 长按识别下方二维码， 按需求添加 扫码关注添加客服 进Python社群▲ 扫码关注添加客服 进Java社群 ▲ 英文：Fabio Manganiello， 翻译：Python开发者 / 字符串拼接工程师 我有一阵子没更新文章了。是因为我当爹啦，必须放下手头的工作，转而处理一些尚未自动化的育儿任务。 换个角度想，这些没自动化的任务，是否可以做成自动化的呢？虽然机器人换尿布还要好几年才能实现，但是目前有一些比较简单的育儿任务可以自动化掉。 当了爹后我发现，宝宝真的经常哭。即使我在家里，我可能也不会总是在附近听到我儿子的哭声。商用婴儿监视器通常会填补这一空白，它们就像对讲机，即使你在其他房间也能听到宝宝的声音。但我很快意识到，商用婴儿监视器比我想要的理想设备要笨得多。它们并不能检测宝宝的哭声，只是像对讲机一样把声音从声源传到扬声器。父母在不同屋子里活动的时候必须带着扬声器，否则在其他房间 就听不到声音了。商用婴儿监视器通常带有低功率的扬声器，而且还不能连接到外接扬声器 —— 这意味着如果我在另一个房间里播放音乐，就算我带着监视器，我也可能会听不到宝宝的哭声。 我理想中的婴儿监控器是这样的： 它要在廉价设备上运行，比如外接廉价 USB 麦克风的树莓派。 它要能够检测婴儿哭声，并在他开始或停止哭的时候通知我（最好通知发手机上）、或者把哭声记录到仪表盘上

ValueError: Feature not in features dictionary

由 你。 提交于 2020-12-25 08:30:34
问题 I am attempting to write a simple deep machine learning model using TensorFlow. I'm using a toy dataset I made up in Excel just to get the model working and accepting data. My code is as follows: import pandas as pd import numpy as np import tensorflow as tf raw_data = np.genfromtxt('ai/mock-data.csv', delimiter=',', dtype=str) my_data = np.delete(raw_data, (0), axis=0) #deletes the first row, axis=0 indicates row, axis=1 indicates column my_data = np.delete(my_data, (0), axis=1) #deletes the

ValueError: Feature not in features dictionary

由 ￡可爱￡侵袭症＋ 提交于 2020-12-25 08:29:47
问题 I am attempting to write a simple deep machine learning model using TensorFlow. I'm using a toy dataset I made up in Excel just to get the model working and accepting data. My code is as follows: import pandas as pd import numpy as np import tensorflow as tf raw_data = np.genfromtxt('ai/mock-data.csv', delimiter=',', dtype=str) my_data = np.delete(raw_data, (0), axis=0) #deletes the first row, axis=0 indicates row, axis=1 indicates column my_data = np.delete(my_data, (0), axis=1) #deletes the

ValueError: Feature not in features dictionary

由 和自甴很熟 提交于 2020-12-25 08:26:50
问题 I am attempting to write a simple deep machine learning model using TensorFlow. I'm using a toy dataset I made up in Excel just to get the model working and accepting data. My code is as follows: import pandas as pd import numpy as np import tensorflow as tf raw_data = np.genfromtxt('ai/mock-data.csv', delimiter=',', dtype=str) my_data = np.delete(raw_data, (0), axis=0) #deletes the first row, axis=0 indicates row, axis=1 indicates column my_data = np.delete(my_data, (0), axis=1) #deletes the

Tensorflow error using tf.image.random : 'numpy.ndarray' object has no attribute 'get_shape'

由 懵懂的女人 提交于 2020-12-25 04:24:14
问题 Intro I am using a modified version of the Tensorflow tutorial "Deep MNIST for experts" with the Python API for a medical images classification project using convolutionnal networks. I want to artificially increase the size of my training set by applying random modifications on the images of my training set. Problem When I run the line : flipped_images = tf.image.random_flip_left_right(images) I get de following error : AttributeError: 'numpy.ndarray' object has no attribute 'get_shape' My

Tensorflow error using tf.image.random : 'numpy.ndarray' object has no attribute 'get_shape'

由 匆匆过客 提交于 2020-12-25 04:23:59
问题 Intro I am using a modified version of the Tensorflow tutorial "Deep MNIST for experts" with the Python API for a medical images classification project using convolutionnal networks. I want to artificially increase the size of my training set by applying random modifications on the images of my training set. Problem When I run the line : flipped_images = tf.image.random_flip_left_right(images) I get de following error : AttributeError: 'numpy.ndarray' object has no attribute 'get_shape' My

AttributeError: module 'tensorflow' has no attribute 'get_default_graph'

由 与世无争的帅哥 提交于 2020-12-25 04:12:21
问题 I am doing some task related to image captioning and I have loaded the weights of inception model like this model = InceptionV3(weights='imagenet') But I am getting error like this: AttributeError: module 'tensorflow' has no attribute 'get_default_graph' What should I do? Please help. Here is the full output of above code. 1 . --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) in () 1 # Load the inception v3 model ---->
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