amobiny

import tensorflow as tf
tf.reset_default_graph()   # To clear the defined variables and operations of the previous cell
# create the variables
w_gs = tf.get_variable('W_Grayscale', shape=[30, 10], initializer=tf.truncated_normal_initializer(mean=0, stddev=1))
w_c = tf.get_variable('W_Color', shape=[50, 30], initializer=tf.truncated_normal_initializer(mean=0, stddev=1))
# ___step 0:___ reshape it to 4D-tensors
w_gs_reshaped = tf.reshape(w_gs, (3, 10, 10, 1))
w_c_reshaped = tf.reshape(w_c, (5, 10, 10, 3))
# ____step 1:____ create the summaries
gs_summary = tf.summary.image('Grayscale', w_gs_reshaped)

amobiny

# create the variables
x_scalar = tf.get_variable('x_scalar', shape=[], initializer=tf.truncated_normal_initializer(mean=0, stddev=1))
x_matrix = tf.get_variable('x_matrix', shape=[30, 40], initializer=tf.truncated_normal_initializer(mean=0, stddev=1))
# ____step 1:____ create the summaries
# A scalar summary for the scalar tensor
scalar_summary = tf.summary.scalar('My_scalar_summary', x_scalar)
# A histogram summary for the non-scalar (i.e. 2D or matrix) tensor
histogram_summary = tf.summary.histogram('My_histogram_summary', x_matrix)
# ____step 2:____ merge all summaries
merged = tf.summary.merge_all()

amobiny

import tensorflow as tf
tf.reset_default_graph()   # To clear the defined variables and operations of the previous cell
# create the variables
x_scalar = tf.get_variable('x_scalar', shape=[], initializer=tf.truncated_normal_initializer(mean=0, stddev=1))
x_matrix = tf.get_variable('x_matrix', shape=[30, 40], initializer=tf.truncated_normal_initializer(mean=0, stddev=1))
# ____step 1:____ create the summaries
# A scalar summary for the scalar tensor
scalar_summary = tf.summary.scalar('My_scalar_summary', x_scalar)
# A histogram summary for the non-scalar (i.e. 2D or matrix) tensor
histogram_summary = tf.summary.histogram('My_histogram_summary', x_matrix)

amobiny

import tensorflow as tf
tf.reset_default_graph()   # To clear the defined variables and operations of the previous cell
# create the scalar variable
x_scalar = tf.get_variable('x_scalar', shape=[], initializer=tf.truncated_normal_initializer(mean=0, stddev=1))
# ____step 1:____ create the scalar summary
first_summary = tf.summary.scalar(name='My_first_scalar_summary', tensor=x_scalar)
init = tf.global_variables_initializer()
# launch the graph in a session
with tf.Session() as sess:
    # ____step 2:____ creating the writer inside the session

amobiny

import tensorflow as tf
tf.reset_default_graph()   # To clear the defined variables and operations of the previous cell
# create graph
a = tf.constant(2, name="a")
b = tf.constant(3, name="b")
c = tf.add(a, b, name="addition")
# creating the writer out of the session
# writer = tf.summary.FileWriter('./graphs', tf.get_default_graph())
# launch the graph in a session
with tf.Session() as sess:

amobiny

import tensorflow as tf
tf.reset_default_graph()   # To clear the defined variables and operations of the previous cell
# create graph
a = tf.constant(2)
b = tf.constant(3)
c = tf.add(a, b)
# creating the writer out of the session
# writer = tf.summary.FileWriter('./graphs', tf.get_default_graph())
# launch the graph in a session
with tf.Session() as sess:

amobiny

import tensorflow as tf
# create graph
a = tf.constant(2)
b = tf.constant(3)
c = tf.add(a, b)
# launch the graph in a session
with tf.Session() as sess:
    print(sess.run(c))