ValueError: Tensor conversion requested dtype int32 for Tensor with dtype float32: <tf.Tensor 'shuffle_batch/sub/y:0' shape=() dtype=float32>

[HaFred]

When I tried to run the Top.py, exceptions are shown as below:

2020-11-12 03:39:21 

import time
import tensorflow as tf

debug = False
Time = time.strftime('%Y-%m-%d', time.localtime())
# Notes = 'vgg7 2888'
Notes = 'temp'

GPU = [0]
batchSize = 128

dataSet = 'CIFAR10'

loadModel = None
# loadModel = '../model/' + '2017-12-06' + '(' + 'vgg7 2888' + ')' + '.tf'
saveModel = None
# saveModel = '../model/' + Time + '(' + Notes + ')' + '.tf'

bitsW = 2  # bit width of we ights
bitsA = 8  # bit width of activations
bitsG = 8  # bit width of gradients
bitsE = 8  # bit width of errors

bitsR = 16  # bit width of randomizer

lr = tf.Variable(initial_value=0., trainable=False, name='lr', dtype=tf.float32)
lr_schedule = [0, 8, 200, 1,250,1./8,300,0]

L2 = 0

lossFunc = 'SSE'
# lossFunc = tf.losses.softmax_cross_entropy
optimizer = tf.compat.v1.train.GradientDescentOptimizer(1)  # lr is controlled in Quantize.G
# optimizer = tf.train.MomentumOptimizer(lr, 0.9, use_nesterov=True)

# shared variables, defined by other files
seed = None
sess = None
W_scale = []

WARNING:tensorflow:From /content/drive/My Drive/workspace/wage/source/getData.py:46: The name tf.FIFOQueue is deprecated. Please use tf.queue.FIFOQueue instead.

WARNING:tensorflow:From /content/drive/My Drive/workspace/wage/source/getData.py:49: QueueRunner.__init__ (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.
Instructions for updating:
To construct input pipelines, use the `tf.data` module.
WARNING:tensorflow:From /content/drive/My Drive/workspace/wage/source/getData.py:50: add_queue_runner (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.
Instructions for updating:
To construct input pipelines, use the `tf.data` module.
WARNING:tensorflow:From /content/drive/My Drive/workspace/wage/source/getData.py:9: The name tf.image.resize_image_with_crop_or_pad is deprecated. Please use tf.image.resize_with_crop_or_pad instead.

WARNING:tensorflow:From /content/drive/My Drive/workspace/wage/source/getData.py:10: The name tf.random_crop is deprecated. Please use tf.image.random_crop instead.

WARNING:tensorflow:From /content/drive/My Drive/workspace/wage/source/getData.py:59: shuffle_batch (from tensorflow.python.training.input) is deprecated and will be removed in a future version.
Instructions for updating:
Queue-based input pipelines have been replaced by `tf.data`. Use `tf.data.Dataset.shuffle(min_after_dequeue).batch(batch_size)`.
Traceback (most recent call last):
  File "/tensorflow-1.15.2/python3.6/tensorflow_core/python/framework/op_def_library.py", line 528, in _apply_op_helper
    preferred_dtype=default_dtype)
  File "/tensorflow-1.15.2/python3.6/tensorflow_core/python/framework/ops.py", line 1273, in internal_convert_to_tensor
    (dtype.name, value.dtype.name, value))
ValueError: Tensor conversion requested dtype int32 for Tensor with dtype float32: <tf.Tensor 'shuffle_batch/sub/y:0' shape=() dtype=float32>

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "Top.py", line 167, in <module>
    main()
  File "Top.py", line 47, in main
    getData.loadData(Option.dataSet,batchSize,numThread)
  File "/content/drive/My Drive/workspace/wage/source/getData.py", line 25, in loadData
    trainX, trainY = data2Queue(numpyTrainX, numpyTrainY, batchSize,numThread, True,True)
  File "/content/drive/My Drive/workspace/wage/source/getData.py", line 59, in data2Queue
    seed=seed)
  File "/tensorflow-1.15.2/python3.6/tensorflow_core/python/util/deprecation.py", line 324, in new_func
    return func(*args, **kwargs)
  File "/tensorflow-1.15.2/python3.6/tensorflow_core/python/training/input.py", line 1347, in shuffle_batch
    name=name)
  File "/tensorflow-1.15.2/python3.6/tensorflow_core/python/training/input.py", line 862, in _shuffle_batch
    math_ops.maximum(0, queue.size() - min_after_dequeue), dtypes.float32) *
  File "/tensorflow-1.15.2/python3.6/tensorflow_core/python/ops/math_ops.py", line 912, in binary_op_wrapper
    return func(x, y, name=name)
  File "/tensorflow-1.15.2/python3.6/tensorflow_core/python/ops/gen_math_ops.py", line 11086, in sub
    "Sub", x=x, y=y, name=name)
  File "/tensorflow-1.15.2/python3.6/tensorflow_core/python/framework/op_def_library.py", line 564, in _apply_op_helper
    inferred_from[input_arg.type_attr]))
TypeError: Input 'y' of 'Sub' Op has type float32 that does not match type int32 of argument 'x'.
Exception ignored in: <Log.Log object at 0x7f5a34dfeba8>
AttributeError: 'Log' object has no attribute 'flush'