Python print_operation_value примеры использования

Пример #1

Файл: string_to_number.py Проект: hwauni/machine_learning

# -*- coding: utf-8 -*-
#!/usr/bin/python

import tensorflow as tf
import tfutil


var = tf.Variable("1", dtype=tf.string)
tfutil.print_variable(var)
print(var)
num1 = tf.string_to_number(var, out_type=tf.int32)
tfutil.print_operation_value(num1)
print(num1)

const = tf.constant("2", dtype=tf.string)
tfutil.print_constant(const)
print(const)
num2 = tf.string_to_number(const, out_type=tf.float32)
tfutil.print_operation_value(num2)
print(num2)

Пример #2

Файл: extract_image_patches.py Проект: hwauni/machine_learning

tfutil.print_constant(const1)

# Ksizes Test
# output_depth = ksize_rows * ksize_cols * depth = (1 x 1 x 1 ) = 1
# ksizes: raws: [1] col: [1]
ksizes = [1, 1, 1, 1]
strides = [1, 3, 3, 1]
rates = [1, 1, 1, 1]
exi_const1 = tf.extract_image_patches(const1,
                                      ksizes,
                                      strides,
                                      rates,
                                      padding='VALID')
print(exi_const1)
print(tf.shape(exi_const1))
tfutil.print_operation_value(exi_const1)

# Ksizes Test
# output_depth = ksize_rows * ksize_cols * depth = (1 x 2 x 1 ) = 2
# ksizes: raws: [1, 2]  col: [1, 2]
ksizes = [1, 1, 2, 1]
strides = [1, 3, 3, 1]
rates = [1, 1, 1, 1]
exi_const1 = tf.extract_image_patches(const1,
                                      ksizes,
                                      strides,
                                      rates,
                                      padding='VALID')
print(exi_const1)
print(tf.shape(exi_const1))
tfutil.print_operation_value(exi_const1)

Пример #3

Файл: split.py Проект: hwauni/machine_learning

#!/usr/bin/python

import tensorflow as tf
import numpy as np
import tfutil

# [1, 2, 3, 4, 5, 6, 7, 8, 9]
const1 = tf.constant(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]), dtype=tf.int32)
print(const1)
print(tf.shape(const1))
tfutil.print_constant(const1)

sp1_const1, sp2_const1 = tf.split(const1, 2, 0)
print(sp1_const1)
print(tf.shape(sp1_const1))
tfutil.print_operation_value(sp1_const1)

print(sp2_const1)
print(tf.shape(sp2_const1))
tfutil.print_operation_value(sp2_const1)

# [[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]], [[13, 14, 15], [16, 17, 18]]]
const2 = tf.constant([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12],
                      [13, 14, 15, 16], [17, 18, 19, 20]])
print(const2)
print(tf.shape(const2))
tfutil.print_constant(const2)

sp1_const2, sp2_const2 = tf.split(const2, 2, 1)
print(sp1_const2)
print(tf.shape(sp1_const2))

Пример #4

Файл: space_to_batch.py Проект: hwauni/machine_learning

const1 = tf.constant(np.array(x), dtype=tf.int32)
print(const1)
print(tf.shape(const1))
tfutil.print_constant(const1)

# return: [batch*block_size*block_size, height_pad/block_size, width_pad/block_size, depth]
# paddings = [[pad_top, pad_bottom], [pad_left, pad_right]]
# height_pad = pad_top + height + pad_bottom
# width_pad = pad_left + width + pad_right
# blocksize = Both height_pad and width_pad must be divisible by block_size.
paddings = [[0, 0], [0, 0]]
blocksize = 1
stb_const1 = tf.space_to_batch(const1, paddings, blocksize)
print(stb_const1)
print(tf.shape(stb_const1))
tfutil.print_operation_value(stb_const1)

paddings = [[0, 0], [0, 1]]
blocksize = 1
stb_const1 = tf.space_to_batch(const1, paddings, blocksize)
print(stb_const1)
print(tf.shape(stb_const1))
tfutil.print_operation_value(stb_const1)

paddings = [[0, 0], [1, 1]]
blocksize = 1
stb_const1 = tf.space_to_batch(const1, paddings, blocksize)
print(stb_const1)
print(tf.shape(stb_const1))
tfutil.print_operation_value(stb_const1)

Пример #5

Файл: unstack.py Проект: hwauni/machine_learning

tfutil.print_constant(const1)

const2 = tf.constant(np.array([4, 5, 6]), dtype=tf.int32)
print(const2)
print(tf.shape(const2))
tfutil.print_constant(const2)

const3 = tf.constant(np.array([7, 8, 9]), dtype=tf.int32)
print(const3)
print(tf.shape(const3))
tfutil.print_constant(const3)

pack_const1 = tf.stack([const1, const2, const3])
print(pack_const1)
print(tf.shape(pack_const1))
tfutil.print_operation_value(pack_const1)

up_const1, up_const2, up_const3 = tf.unstack(pack_const1)
print(up_const1)
print(tf.shape(up_const1))
tfutil.print_constant(up_const1)

print(up_const2)
print(tf.shape(up_const2))
tfutil.print_constant(up_const2)

print(up_const3)
print(tf.shape(up_const3))
tfutil.print_constant(up_const3)

pack_const1 = tf.stack([const1, const2, const3], axis=1)

Пример #6

Файл: to_float.py Проект: hwauni/machine_learning

# -*- coding: utf-8 -*-
#!/usr/bin/python

import tensorflow as tf
import tfutil

const1 = tf.constant(1)
tfutil.print_constant(const1)
print(const1)
float1 = tf.to_float(const1)
tfutil.print_operation_value(float1)
print(float1)

const2 = tf.constant([2, 3])
tfutil.print_constant(const2)
print(const2)
float2 = tf.to_float(const2)
tfutil.print_operation_value(float2)
print(float2)

var1 = tf.Variable(4)
tfutil.print_variable(var1)
print(var1)
float3 = tf.to_float(var1)
tfutil.print_operation_value(float3)
print(float3)

var2 = tf.Variable([5, 6])
tfutil.print_variable(var2)
print(var2)
float4 = tf.to_float(var2)

Пример #7

Файл: to_int32.py Проект: hwauni/machine_learning

# -*- coding: utf-8 -*-
#!/usr/bin/python

import tensorflow as tf
import tfutil

const1 = tf.constant(1, dtype=tf.float32)
tfutil.print_constant(const1)
print(const1)
int32_1 = tf.to_int32(const1)
tfutil.print_operation_value(int32_1)
print(int32_1)

const2 = tf.constant([2, 3], dtype=tf.float32)
tfutil.print_constant(const2)
print(const2)
int32_2 = tf.to_int32(const2)
tfutil.print_operation_value(int32_2)
print(int32_2)

var1 = tf.Variable(4, dtype=tf.float32)
tfutil.print_variable(var1)
print(var1)
int32_3 = tf.to_int32(var1)
tfutil.print_operation_value(int32_3)
print(int32_3)

var2 = tf.Variable([5, 6], dtype=tf.float32)
tfutil.print_variable(var2)
print(var2)
int32_4 = tf.to_int32(var2)

Пример #8

Файл: cast.py Проект: hwauni/machine_learning

# -*- coding: utf-8 -*-
#!/usr/bin/python

import tensorflow as tf
import tfutil

const1 = tf.constant(127, dtype=tf.int32)
tfutil.print_constant(const1)
print(const1)
f32 = tf.cast(const1, tf.float32)
tfutil.print_operation_value(f32)
print(f32)
f64 = tf.cast(const1, tf.float64)
tfutil.print_operation_value(f64)
print(f64)
i8 = tf.cast(const1, tf.int8)
tfutil.print_operation_value(i8)
print(i8)
i16 = tf.cast(const1, tf.int16)
tfutil.print_operation_value(i16)
print(i16)
i64 = tf.cast(const1, tf.int64)
tfutil.print_operation_value(i64)
print(i64)
u8 = tf.cast(const1, tf.uint8)
tfutil.print_operation_value(u8)
print(u8)
''' 
# not support
s = tf.cast(const1, tf.string)
tfutil.print_operation_value(s)

Пример #9

Файл: dynamic_partition.py Проект: hwauni/machine_learning

# outputs[i].shape = [sum(partitions == i)] + data.shape[partitions.ndim:]
# outputs[i] = pack([data[js, ...] for js if partitions[js] == i])

x = [10, 20]
const1 = tf.constant(np.array(x))
print(const1)
print(tf.shape(const1))
tfutil.print_constant(const1)

# Scalar partitions.
partitions = 1
num_partitions = 2
dyp_const1 = tf.dynamic_partition(const1, partitions, num_partitions)
print(dyp_const1[0])
print(tf.shape(dyp_const1[0]))
tfutil.print_operation_value(dyp_const1[0])

print(dyp_const1[1])
print(tf.shape(dyp_const1[1]))
tfutil.print_operation_value(dyp_const1[1])

print(dyp_const1)
print(tf.shape(dyp_const1))
tfutil.print_operation_value(dyp_const1)

x = [10, 20, 30, 40, 50]
const2 = tf.constant(np.array(x))
print(const2)
print(tf.shape(const2))
tfutil.print_constant(const2)

Пример #10

Файл: reverse.py Проект: hwauni/machine_learning

import tensorflow as tf
import numpy as np
import tfutil

x = [[[[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]],
      [[12, 13, 14, 15], [16, 17, 18, 19], [20, 21, 22, 23]]]]

const1 = tf.constant(np.array(x), dtype=tf.int32)
print(const1)
print(tf.shape(const1))
tfutil.print_constant(const1)

dims = [3]
dims_const1 = tf.reverse(const1, dims)
print(dims_const1)
print(tf.shape(dims_const1))
tfutil.print_operation_value(dims_const1)

dims = [1]
dims_const1 = tf.reverse(const1, dims)
print(dims_const1)
print(tf.shape(dims_const1))
tfutil.print_operation_value(dims_const1)

dims = [2]
dims_const1 = tf.reverse(const1, dims)
print(dims_const1)
print(tf.shape(dims_const1))
tfutil.print_operation_value(dims_const1)

Пример #11

# Vector indices:
  merged[indices[m][i], ...] = data[m][i, ...]
merged.shape = [max(indices)] + constant
'''

x = [[1, 2], [3, 4]]
const1 = tf.constant(np.array(x))
print(const1)
print(tf.shape(const1))
tfutil.print_constant(const1)

indice = [[0, 1], [2, 3]]
dys_const1 = tf.dynamic_stitch(indice, const1)
print(dys_const1[0])
print(tf.shape(dys_const1[0]))
tfutil.print_operation_value(dys_const1[0])

x = [[1, 2], [3, 4]]
const1 = tf.constant(np.array(x))
print(const1)
print(tf.shape(const1))
tfutil.print_constant(const1)

y = [1, 1]
row_to_add = tf.constant(np.array(y))
print(row_to_add)
print(tf.shape(row_to_add))
tfutil.print_constant(row_to_add)

original_row = const1[0]
print(original_row)

Пример #12

# -*- coding: utf-8 -*-
#!/usr/bin/python

import tensorflow as tf
import tfutil

const1 = tf.constant([1, 2, 3, 4, 5, 6, 7, 8, 9])
print(const1)
tfutil.print_constant(const1)
rs_const1 = tf.reshape(const1, [3, 3])
print(rs_const1)
tfutil.print_operation_value(rs_const1)

const2 = tf.constant([[[1, 1], [2, 2]], [[3, 3], [4, 4]]])
print(const2)
tfutil.print_constant(const2)
rs_const2 = tf.reshape(const2, [2, 4])
print(rs_const2)
tfutil.print_operation_value(rs_const2)

const3 = tf.constant([[[1, 1, 1], [2, 2, 2]], [[3, 3, 3], [4, 4, 4]],
                      [[5, 5, 5], [6, 6, 6]]])
print(const3)
tfutil.print_constant(const3)
rs_const3 = tf.reshape(const3, [-1])
print(rs_const3)
tfutil.print_operation_value(rs_const3)

const4 = tf.constant([1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6])
print(const4)
tfutil.print_constant(const4)

Пример #13

# -*- coding: utf-8 -*-
#!/usr/bin/python

import tensorflow as tf
import tfutil

const1 = tf.constant(1)
tfutil.print_constant(const1)
print(const1)
tfutil.print_operation_value(tf.shape(const1))

const2 = tf.constant([1, 2])
tfutil.print_constant(const2)
print(const2)
tfutil.print_operation_value(tf.shape(const2))

const3 = tf.constant([[1, 2], [3, 4]])
tfutil.print_constant(const3)
print(const3)
tfutil.print_operation_value(tf.shape(const3))

const4 = tf.constant([[1, 2], [3, 4], [5, 6]])
tfutil.print_constant(const4)
print(const4)
tfutil.print_operation_value(tf.shape(const4))

const5 = tf.constant([[[1], [2]], [[3], [4]]])
tfutil.print_constant(const5)
print(const5)
tfutil.print_operation_value(tf.shape(const5))

Пример #14

# -*- coding: utf-8 -*-
#!/usr/bin/python

import tensorflow as tf
import tfutil

const1, const2 = tf.constant([1]), tf.constant([2, 3])
var1, var2 = tf.Variable([4]), tf.Variable([5, 6])

tfutil.print_constant(const1)
tfutil.print_constant(const2)
tfutil.print_variable(var1)
tfutil.print_variable(var2)

print('add operation section')
tfutil.print_operation_value(tf.add(const1, var1))
tfutil.print_operation_value(tf.add(const2, var2))

print('subtract operation section')
tfutil.print_operation_value(tf.subtract(const1, var1))
tfutil.print_operation_value(tf.subtract(const2, var2))

print('multiply operation section')
tfutil.print_operation_value(tf.multiply(const1, var1))
tfutil.print_operation_value(tf.multiply(const2, var2))

print('div operation section')
tfutil.print_operation_value(tf.div(const1, var1))
tfutil.print_operation_value(tf.div(const2, var2))

print('mod operation section')

Пример #15

Файл: bitcast.py Проект: hwauni/machine_learning

# -*- coding: utf-8 -*-
#!/usr/bin/python

import tensorflow as tf
import numpy as np
import tfutil

x = 37.0
const1 = tf.constant(x)
print(const1)
print(tf.shape(const1))
tfutil.print_constant(const1)

bc_const1 = tf.bitcast(const1, tf.int32)
print(bc_const1)
print(tf.shape(bc_const1))
tfutil.print_operation_value(bc_const1)

x = -1
invert_bits = tf.constant(x) - bc_const1
print(invert_bits)
print(tf.shape(invert_bits))
tfutil.print_operation_value(invert_bits)

bc_to_float = tf.bitcast(invert_bits, tf.float32)
print(bc_to_float)
print(tf.shape(bc_to_float))
tfutil.print_operation_value(bc_to_float)

Пример #16

Файл: boolean_mask.py Проект: hwauni/machine_learning

# -*- coding: utf-8 -*-
#!/usr/bin/python

import tensorflow as tf
import numpy as np
import tfutil

x = [0, 1, 2, 3]
const1 = tf.constant(np.array(x))
print(const1)
print(tf.shape(const1))
tfutil.print_constant(const1)

mask = np.array([True, False, True, False])
bm_const1 = tf.boolean_mask(const1, mask)
print(bm_const1)
print(tf.shape(bm_const1))
tfutil.print_operation_value(bm_const1)

x = [[1, 2], [3, 4], [5, 6]]
const2 = tf.constant(np.array(x))
print(const2)
print(tf.shape(const2))
tfutil.print_constant(const2)

mask = np.array([True, False, True])
bm_const2 = tf.boolean_mask(const2, mask)
print(bm_const2)
print(tf.shape(bm_const2))
tfutil.print_operation_value(bm_const2)

Пример #17

Файл: to_double.py Проект: hwauni/machine_learning

# -*- coding: utf-8 -*-
#!/usr/bin/python

import tensorflow as tf
import tfutil

const1 = tf.constant(1)
tfutil.print_constant(const1)
print(const1)
double1 = tf.to_double(const1)
tfutil.print_operation_value(double1)
print(double1)

const2 = tf.constant([2, 3])
tfutil.print_constant(const2)
print(const2)
double2 = tf.to_double(const2)
tfutil.print_operation_value(double2)
print(double2)

var1 = tf.Variable(4)
tfutil.print_variable(var1)
print(var1)
double3 = tf.to_double(var1)
tfutil.print_operation_value(double3)
print(double3)

var2 = tf.Variable([5, 6])
tfutil.print_variable(var2)
print(var2)
double4 = tf.to_double(var2)

Пример #18

# -*- coding: utf-8 -*-
#!/usr/bin/python

import tensorflow as tf
import numpy as np
import tfutil

# [[1, 2, 3], [4, 5, 6]]
# [[7, 8, 9], [10, 11, 12]]
const1 = tf.constant(np.array([[1, 2, 3], [4, 5, 6]]), dtype=tf.int32)
print(const1)
print(tf.shape(const1))
tfutil.print_constant(const1)
const2 = tf.constant(np.array([[7, 8, 9], [10, 11, 12]]), dtype=tf.int32)
print(const2)
print(tf.shape(const2))
tfutil.print_constant(const2)

cc_const1 = tf.concat([const1, const2], 0)
print(cc_const1)
print(tf.shape(cc_const1))
tfutil.print_operation_value(cc_const1)

cc_const1 = tf.concat([const1, const2], 1)
print(cc_const1)
print(tf.shape(cc_const1))
tfutil.print_operation_value(cc_const1)

Пример #19

import tensorflow as tf
import numpy as np
import tfutil

x = [[[[1, 2, 3, 4]]]]

const1 = tf.constant(np.array(x), dtype=tf.int32)
print(const1)
print(tf.shape(const1))
tfutil.print_constant(const1)

blocksize = 2
dts_const1 = tf.depth_to_space(const1, blocksize)
print(dts_const1)
print(tf.shape(dts_const1))
tfutil.print_operation_value(dts_const1)

x = [[[[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]]]]
const2 = tf.constant(np.array(x), dtype=tf.int32)
print(const2)
print(tf.shape(const2))
tfutil.print_constant(const2)

blocksize = 2
dts_const2 = tf.depth_to_space(const2, blocksize)
print(dts_const2)
print(tf.shape(dts_const2))
tfutil.print_operation_value(dts_const2)

x = [[[[1, 2, 3, 4], [5, 6, 7, 8]], [[9, 10, 11, 12], [13, 14, 15, 16]]]]
const3 = tf.constant(np.array(x), dtype=tf.int32)

Пример #20

const1 = tf.constant(np.array(x), dtype=tf.int32)
print(const1)
print(tf.shape(const1))
tfutil.print_constant(const1)

# crops = [[crop_top, crop_bottom], [crop_left, crop_right]]
# [batch, height, width, depth]
# height = height_pad - crop_top - crop_bottom
# width = width_pad - crop_left - crop_right

corps = [[0, 0],[0, 1]]
blocksize = 1
bts_const1 = tf.batch_to_space(const1, corps, blocksize)
print(bts_const1)
print(tf.shape(bts_const1))
tfutil.print_operation_value(bts_const1)

corps = [[0, 0],[0, 1]]
blocksize = 1
bts_const1 = tf.batch_to_space(const1, corps, blocksize)
print(bts_const1)
print(tf.shape(bts_const1))
tfutil.print_operation_value(bts_const1)

corps = [[0, 1],[0, 0]]
blocksize = 1
bts_const1 = tf.batch_to_space(const1, corps, blocksize)
print(bts_const1)
print(tf.shape(bts_const1))
tfutil.print_operation_value(bts_const1)