TensorFlow broadcasting

本文最后更新于:3 年前

Reference


broadcasting

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arr = tf.range(60)
arr1 = tf.reshape(arr, [3, 4, 5])
t = tf.cast(arr1, dtype=tf.float32)
t1 = tf.ones(5)
t2 = tf.ones([4, 1])
t3 = tf.ones([3, 4, 1])
t11 = t + t1
t21 = t + t2
t31 = t + t3
print(t) # tf.Tensor(
# [[[ 0. 1. 2. 3. 4.]
# [ 5. 6. 7. 8. 9.]
# [10. 11. 12. 13. 14.]
# [15. 16. 17. 18. 19.]]
#
# [[20. 21. 22. 23. 24.]
# [25. 26. 27. 28. 29.]
# [30. 31. 32. 33. 34.]
# [35. 36. 37. 38. 39.]]
#
# [[40. 41. 42. 43. 44.]
# [45. 46. 47. 48. 49.]
# [50. 51. 52. 53. 54.]
# [55. 56. 57. 58. 59.]]], shape=(3, 4, 5), dtype=float32)
print(t1) # tf.Tensor([1. 1. 1. 1. 1.], shape=(5,), dtype=float32)
print(t2) # tf.Tensor(
# [[1.]
# [1.]
# [1.]
# [1.]], shape=(4, 1), dtype=float32)
print(t3) # tf.Tensor(
# [[[1.]
# [1.]
# [1.]
# [1.]]
#
# [[1.]
# [1.]
# [1.]
# [1.]]
#
# [[1.]
# [1.]
# [1.]
# [1.]]], shape=(3, 4, 1), dtype=float32)
print(t11) # tf.Tensor(
# [[[ 1. 2. 3. 4. 5.]
# [ 6. 7. 8. 9. 10.]
# [11. 12. 13. 14. 15.]
# [16. 17. 18. 19. 20.]]
#
# [[21. 22. 23. 24. 25.]
# [26. 27. 28. 29. 30.]
# [31. 32. 33. 34. 35.]
# [36. 37. 38. 39. 40.]]
#
# [[41. 42. 43. 44. 45.]
# [46. 47. 48. 49. 50.]
# [51. 52. 53. 54. 55.]
# [56. 57. 58. 59. 60.]]], shape=(3, 4, 5), dtype=float32)
print(t21) # tf.Tensor(
# [[[ 1. 2. 3. 4. 5.]
# [ 6. 7. 8. 9. 10.]
# [11. 12. 13. 14. 15.]
# [16. 17. 18. 19. 20.]]
#
# [[21. 22. 23. 24. 25.]
# [26. 27. 28. 29. 30.]
# [31. 32. 33. 34. 35.]
# [36. 37. 38. 39. 40.]]
#
# [[41. 42. 43. 44. 45.]
# [46. 47. 48. 49. 50.]
# [51. 52. 53. 54. 55.]
# [56. 57. 58. 59. 60.]]], shape=(3, 4, 5), dtype=float32)
print(t31) # tf.Tensor(
# [[[ 1. 2. 3. 4. 5.]
# [ 6. 7. 8. 9. 10.]
# [11. 12. 13. 14. 15.]
# [16. 17. 18. 19. 20.]]
#
# [[21. 22. 23. 24. 25.]
# [26. 27. 28. 29. 30.]
# [31. 32. 33. 34. 35.]
# [36. 37. 38. 39. 40.]]
#
# [[41. 42. 43. 44. 45.]
# [46. 47. 48. 49. 50.]
# [51. 52. 53. 54. 55.]
# [56. 57. 58. 59. 60.]]], shape=(3, 4, 5), dtype=float32)

t4 = tf.ones([3, 4, 2])
t41 = t + t4 # tensorflow.python.framework.errors_impl.InvalidArgumentError: Incompatible shapes: [3,4,5] vs. [3,4,2] [Op:Add] name: add/

broadcast_to

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arr = tf.range(12)
arr1 = tf.reshape(arr, [3, 4, 1])
t = tf.cast(arr1, dtype=tf.float32)
t1 = tf.broadcast_to(t, [3, 4, 5])
print(t) # tf.Tensor(
# [[[ 0.]
# [ 1.]
# [ 2.]
# [ 3.]]
#
# [[ 4.]
# [ 5.]
# [ 6.]
# [ 7.]]
#
# [[ 8.]
# [ 9.]
# [10.]
# [11.]]], shape=(3, 4, 1), dtype=float32)
print(t1) # tf.Tensor(
# [[[ 0. 0. 0. 0. 0.]
# [ 1. 1. 1. 1. 1.]
# [ 2. 2. 2. 2. 2.]
# [ 3. 3. 3. 3. 3.]]
#
# [[ 4. 4. 4. 4. 4.]
# [ 5. 5. 5. 5. 5.]
# [ 6. 6. 6. 6. 6.]
# [ 7. 7. 7. 7. 7.]]
#
# [[ 8. 8. 8. 8. 8.]
# [ 9. 9. 9. 9. 9.]
# [10. 10. 10. 10. 10.]
# [11. 11. 11. 11. 11.]]], shape=(3, 4, 5), dtype=float32)

tile

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arr = tf.range(12)
a = tf.reshape(arr, [3, 4])
a1 = tf.broadcast_to(a, [2, 3, 4])
a2 = tf.expand_dims(a, axis=0)
a21 = tf.tile(a2, [2, 1, 1])
print(a) # tf.Tensor(
# [[ 0 1 2 3]
# [ 4 5 6 7]
# [ 8 9 10 11]], shape=(3, 4), dtype=int32)
print(a1) # tf.Tensor(
# [[[ 0 1 2 3]
# [ 4 5 6 7]
# [ 8 9 10 11]]
#
# [[ 0 1 2 3]
# [ 4 5 6 7]
# [ 8 9 10 11]]], shape=(2, 3, 4), dtype=int32)
print(a2) # tf.Tensor(
# [[[ 0 1 2 3]
# [ 4 5 6 7]
# [ 8 9 10 11]]], shape=(1, 3, 4), dtype=int32)
print(a21) # tf.Tensor(
# [[[ 0 1 2 3]
# [ 4 5 6 7]
# [ 8 9 10 11]]
#
# [[ 0 1 2 3]
# [ 4 5 6 7]
# [ 8 9 10 11]]], shape=(2, 3, 4), dtype=int32)


TensorFlow broadcasting
https://weichao.io/6fd609d4935a/
作者
魏超
发布于
2019年5月14日
更新于
2019年6月4日
许可协议