Tensorflow to achieve mnist handwritten digit recognition error? - Codes Helper

Code:
import tensorflow as tf
import numpy as np
tf.enable_eager_execution ()

class DataLoader ():

def __init__(self):
    mnist = tf.keras.datasets.mnist.load_data(path = "mnist.npz")

    self.train_data = mnist[0][0]
    self.train_data = np.reshape(self.train_data,(self.train_data.shape[0],28*28))
    self.train_labels = mnist[0][1]
    self.eval_data = mnist[1][0]
    self.train_data = np.reshape(self.train_data,(self.train_data.shape[0],28*28))
    self.eval_labels = mnist[1][1]

def get_batch(self, batch_size):
    indexs = np.random.randint(0,self.train_data.shape[0],batch_size)
    return self.train_data[indexs, :], self.train_labels[indexs]

"
class MLP (tf.keras.Modle):
"
class MLP (tf.keras.Model):

def __init__(self):
    super().__init__()
    self.dense1 = tf.keras.layers.Dense(units=100, activation= tf.nn.relu)
    self.dense2 = tf.keras.layers.Dense(units=10,activation =None)

def call(self, inputs):
    x = self.dense1(inputs)
    y = self.dense2(x)
    return y

def predict(self, inputs):
    logits = self(inputs)
    return tf.argmax(logits, axis=-1)

num_batches = 1000
batch_size = 50
learning_rate = 0.001

model = MLP ()
data_loader = DataLoader ()
optimizer = tf.train.AdamOptimizer (learning_rate = learning_rate)

for batch_index in range (num_batches):

X , y = data_loader.get_batch(batch_size)
print(np.shape(X))
with tf.GradientTape() as tape:
    X = tf.convert_to_tensor(X, dtype = tf.int64, name = "X")
    print(X)
    y_logit_pred = model(X)
    loss = tf.losses.sparse_softmax_cross_entropy(labels = y, logits = y_logit_pred)
    print("batch %d: loss %f" % (batch_index, loss.numpy()))

grads = tape.gradient(loss, model.variables)
optimizer.apply_gradients(grads_and_vars = zip(grads, model.variables))

num_eval_samples = np.shape (data_loader.eval_labels) [0]
y_pred = model.predict (data_loader.eval_data). Numpy ()
print ("test accuracy:% f"% (sum (y_pred = = data_loader.eval_labels) / num_eval_samples))

error message:

/ home/kalarea/.conda/envs/py35/bin/python / home/kalarea/PycharmProjects/start_tensorflow/start_tensorflow.py
/ home/kalarea/.conda/envs/py35/lib/python3.5/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from float to np.floating is deprecated. In future, it will be treated as np.float64 = = np.dtype (float). Type .
from. _ conv import register_converters as _ register_converters
(50, I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
tf.Tensor (
[[00.000]
[0000.000]
[0000.000]
.
[0.000000]
[0.000000]
[0.000000]],.)
2018-10-1418Vol. 2818.977966: I tensorflow/core/platform/cpu_feature_guard.cc:141]
tf.Tensor (
[[0.000000]
[0000.000]
[0000.000]
. Shape= (50784), dtype=int64)
Traceback (most recent call last):
File "/ home/kalarea/PycharmProjects/start_tensorflow/start_tensorflow.py", line 55, in < module >

y_logit_pred = model(X)

File "/ home/kalarea/.conda/envs/py35/lib/python3.5/site-packages/tensorflow/python/keras/engine/base_layer.py", line 769, in call

outputs = self.call(inputs, *args, **kwargs)

File "/ home/kalarea/PycharmProjects/start_tensorflow/start_tensorflow.py", line 30, in call

x = self.dense1(inputs)

File "/ home/kalarea/.conda/envs/py35/lib/python3.5/site-packages/tensorflow/python/keras/engine/base_layer.py", line 759, in call

self.build(input_shapes)

File "/ home/kalarea/.conda/envs/py35/lib/python3.5/site-packages/tensorflow/python/keras/layers/core.py", line 921, in build

trainable=True)

File "/ home/kalarea/.conda/envs/py35/lib/python3.5/site-packages/tensorflow/python/keras/engine/base_layer.py", line 586, in add_weight

aggregation=aggregation)

File "/ home/kalarea/.conda/envs/py35/lib/python3.5/site-packages/tensorflow/python/training/checkpointable/base.py", line 591, in _ add_variable_with_custom_getter

**kwargs_for_getter)

File "/ home/kalarea/.conda/envs/py35/lib/python3.5/site-packages/tensorflow/python/keras/engine/base_layer.py", line 1986, in make_variable

aggregation=aggregation)

File "/ home/kalarea/.conda/envs/py35/lib/python3.5/site-packages/tensorflow/python/ops/variables.py", line 145, in call

return cls._variable_call(*args, **kwargs)

File "/ home/kalarea/.conda/envs/py35/lib/python3.5/site-packages/tensorflow/python/ops/variables.py", line 141, in _ variable_call

aggregation=aggregation)

File "/ home/kalarea/.conda/envs/py35/lib/python3.5/site-packages/tensorflow/python/ops/variables.py", line 120, in < lambda >

previous_getter = lambda **kwargs: default_variable_creator(None, **kwargs)

File "/ home/kalarea/.conda/envs/py35/lib/python3.5/site-packages/tensorflow/python/ops/variable_scope.py", line 2434, in default_variable_creator

import_scope=import_scope)

File "/ home/kalarea/.conda/envs/py35/lib/python3.5/site-packages/tensorflow/python/ops/variables.py", line 147, in call

return super(VariableMetaclass, cls).__call__(*args, **kwargs)

File "/ home/kalarea/.conda/envs/py35/lib/python3.5/site-packages/tensorflow/python/ops/resource_variable_ops.py", line 297, in init

constraint=constraint)

File "/ home/kalarea/.conda/envs/py35/lib/python3.5/site-packages/tensorflow/python/ops/resource_variable_ops.py", line 420, in _ init_from_args

initial_value = initial_value()

File "/ home/kalarea/.conda/envs/py35/lib/python3.5/site-packages/tensorflow/python/keras/engine/base_layer.py", line 1970, in < lambda >

shape, dtype=dtype, partition_info=partition_info)

File "/ home/kalarea/.conda/envs/py35/lib/python3.5/site-packages/tensorflow/python/ops/init_ops.py", line 483, in call

shape, -limit, limit, dtype, seed=self.seed)

File "/ home/kalarea/.conda/envs/py35/lib/python3.5/site-packages/tensorflow/python/ops/random_ops.py", line 240, in random_uniform

shape, minval, maxval, seed=seed1, seed2=seed2, name=name)

File "/ home/kalarea/.conda/envs/py35/lib/python3.5/site-packages/tensorflow/python/ops/gen_random_ops.py", line 848, in random_uniform_int

_six.raise_from(_core._status_to_exception(e.code, message), None)

File "< string >", line 3, in raise_from
tensorflow.python.framework.errors_impl.InvalidArgumentError: Need minval < maxval, got 0 > = 0 [Op:RandomUniformInt] name: mlp/dense/kernel/random_uniform/

Process finished with exit code 1