# -*- coding: utf-8 -*- #!/usr/bin/python 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)
# -*- coding: utf-8 -*- #!/usr/bin/python import tensorflow as tf import tfutil if __name__ == '__main__': const = tf.ones([2, 3], tf.int32) tfutil.print_constant(const)
# -*- coding: utf-8 -*- #!/usr/bin/python import tensorflow as tf import tfutil if __name__ == '__main__': norm = tf.random_uniform([2, 3], name="var") tfutil.print_constant(norm)
# -*- coding: utf-8 -*- #!/usr/bin/python import tensorflow as tf import tfutil if __name__ == '__main__': norm1 = tf.random_normal([2, 3], mean=-1, stddev=4) tfutil.print_constant(norm1) norm2 = tf.random_normal([2, 3], seed=1234) tfutil.print_constant(norm2)
import numpy as np import tfutil ''' # merged[indices[m][i, ..., j], ...] = data[m][i, ..., j, ...] # Scalar indices: merged[indices[m], ...] = data[m][...] # 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))
# -*- 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)
# -*- coding: utf-8 -*- #!/usr/bin/python import tensorflow as tf import tfutil if __name__ == '__main__': const = tf.constant([[1, 2], [3, 4], [5, 6]]) tfutil.print_constant(const) shuff = tf.random_shuffle(const) tfutil.print_constant(shuff)
# -*- coding: utf-8 -*- #!/usr/bin/python import tensorflow as tf import numpy as np import tfutil x = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] const1 = tf.constant(np.array(x), dtype=tf.int32) print(const1) print(tf.shape(const1)) tfutil.print_constant(const1) idx_const2 = tf.constant([1, 0, 2]) print(idx_const2) print(tf.shape(idx_const2)) tfutil.print_constant(idx_const2) idx_flattened = tf.range(0, const1.shape[0]) * const1.shape[1] + idx_const2 print(idx_flattened) print(tf.shape(idx_flattened)) tfutil.print_constant(idx_flattened) # partial code 1 print(const1.shape[0]) tmp1 = tf.range(0, const1.shape[0]) print(tmp1) print(tf.shape(tmp1)) tfutil.print_constant(tmp1) # partial code 2