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0

I would like to replace values under condition.

NumPy version would go like this

intensity=np.where(
 np.abs(intensity)<1e-4,
 1e-4,
 intensity)

But TensorFlow has a bit different usage for tf.where()

When I tried this

intensity=tf.where(
 tf.math.abs(intensity)<1e-4,
 1e-4,
 intensity)

I got this error

ValueError: Shapes must be equal rank, but are 0 and 4 for 'Select' (op: 'Select') with input shapes: [?,512,512,1], [], [?,512,512,1].

Does that mean I should 4 dimensional tensor for 1e-4?

python tensorflow

share|improve this question

edited Mar 28 at 11:59

jdehesa

35.3k44 gold badges4343 silver badges6666 bronze badges

asked Mar 28 at 8:58

YoungMin ParkYoungMin Park

30722 silver badges1111 bronze badges

add a comment | 

0

I would like to replace values under condition.

NumPy version would go like this

intensity=np.where(
 np.abs(intensity)<1e-4,
 1e-4,
 intensity)

But TensorFlow has a bit different usage for tf.where()

When I tried this

intensity=tf.where(
 tf.math.abs(intensity)<1e-4,
 1e-4,
 intensity)

I got this error

ValueError: Shapes must be equal rank, but are 0 and 4 for 'Select' (op: 'Select') with input shapes: [?,512,512,1], [], [?,512,512,1].

Does that mean I should 4 dimensional tensor for 1e-4?

python tensorflow

share|improve this question

edited Mar 28 at 11:59

jdehesa

35.3k44 gold badges4343 silver badges6666 bronze badges

asked Mar 28 at 8:58

YoungMin ParkYoungMin Park

30722 silver badges1111 bronze badges

add a comment | 

I would like to replace values under condition.

NumPy version would go like this

intensity=np.where(
 np.abs(intensity)<1e-4,
 1e-4,
 intensity)

But TensorFlow has a bit different usage for tf.where()

When I tried this

intensity=tf.where(
 tf.math.abs(intensity)<1e-4,
 1e-4,
 intensity)

I got this error

ValueError: Shapes must be equal rank, but are 0 and 4 for 'Select' (op: 'Select') with input shapes: [?,512,512,1], [], [?,512,512,1].

Does that mean I should 4 dimensional tensor for 1e-4?

python tensorflow

share|improve this question

edited Mar 28 at 11:59

jdehesa

35.3k44 gold badges4343 silver badges6666 bronze badges

asked Mar 28 at 8:58

YoungMin ParkYoungMin Park

30722 silver badges1111 bronze badges

intensity=np.where(
 np.abs(intensity)<1e-4,
 1e-4,
 intensity)

intensity=tf.where(
 tf.math.abs(intensity)<1e-4,
 1e-4,
 intensity)

ValueError: Shapes must be equal rank, but are 0 and 4 for 'Select' (op: 'Select') with input shapes: [?,512,512,1], [], [?,512,512,1].

share|improve this question

edited Mar 28 at 11:59

jdehesa

35.3k44 gold badges4343 silver badges6666 bronze badges

asked Mar 28 at 8:58

YoungMin ParkYoungMin Park

30722 silver badges1111 bronze badges

share|improve this question

edited Mar 28 at 11:59

jdehesa

35.3k44 gold badges4343 silver badges6666 bronze badges

asked Mar 28 at 8:58

YoungMin ParkYoungMin Park

30722 silver badges1111 bronze badges

edited Mar 28 at 11:59

jdehesa

35.3k44 gold badges4343 silver badges6666 bronze badges

edited Mar 28 at 11:59

jdehesa

35.3k44 gold badges4343 silver badges6666 bronze badges

asked Mar 28 at 8:58

YoungMin ParkYoungMin Park

30722 silver badges1111 bronze badges

asked Mar 28 at 8:58

YoungMin ParkYoungMin Park

30722 silver badges1111 bronze badges

1 Answer
1

active

oldest

votes

1

Following code passed the error

# Create an array which has small value (1e-4), 
# whose shape is (2,512,512,1)
small_val=np.full((2,512,512,1),1e-4).astype("float32")

# Convert numpy array to tf.constant
small_val=tf.constant(small_val)

# Use tf.where()
intensity=tf.where(
 tf.math.abs(intensity)<1e-4,
 small_val,
 intensity)

# Error doesn't occur
print(intensity.shape)
# (2, 512, 512, 1)

share|improve this answer

edited Mar 28 at 9:22

AkshayNevrekar

6,9531212 gold badges2323 silver badges4545 bronze badges

answered Mar 28 at 9:09

YoungMin ParkYoungMin Park

30722 silver badges1111 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  You can also directly do small_val = tf.full(tf.shape(intensity), tf.constant(1e-4, dtype=intensity.dtype)), or even just small_val = 1e-4 + tf.zeros_(intensity).
  
  – jdehesa
  Mar 28 at 12:06
  

  
  
  
  

add a comment | 

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1

Following code passed the error

# Create an array which has small value (1e-4), 
# whose shape is (2,512,512,1)
small_val=np.full((2,512,512,1),1e-4).astype("float32")

# Convert numpy array to tf.constant
small_val=tf.constant(small_val)

# Use tf.where()
intensity=tf.where(
 tf.math.abs(intensity)<1e-4,
 small_val,
 intensity)

# Error doesn't occur
print(intensity.shape)
# (2, 512, 512, 1)

share|improve this answer

edited Mar 28 at 9:22

AkshayNevrekar

6,9531212 gold badges2323 silver badges4545 bronze badges

answered Mar 28 at 9:09

YoungMin ParkYoungMin Park

30722 silver badges1111 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  You can also directly do small_val = tf.full(tf.shape(intensity), tf.constant(1e-4, dtype=intensity.dtype)), or even just small_val = 1e-4 + tf.zeros_(intensity).
  
  – jdehesa
  Mar 28 at 12:06
  

  
  
  
  

add a comment | 

1

Following code passed the error

# Create an array which has small value (1e-4), 
# whose shape is (2,512,512,1)
small_val=np.full((2,512,512,1),1e-4).astype("float32")

# Convert numpy array to tf.constant
small_val=tf.constant(small_val)

# Use tf.where()
intensity=tf.where(
 tf.math.abs(intensity)<1e-4,
 small_val,
 intensity)

# Error doesn't occur
print(intensity.shape)
# (2, 512, 512, 1)

share|improve this answer

edited Mar 28 at 9:22

AkshayNevrekar

6,9531212 gold badges2323 silver badges4545 bronze badges

answered Mar 28 at 9:09

YoungMin ParkYoungMin Park

30722 silver badges1111 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  You can also directly do small_val = tf.full(tf.shape(intensity), tf.constant(1e-4, dtype=intensity.dtype)), or even just small_val = 1e-4 + tf.zeros_(intensity).
  
  – jdehesa
  Mar 28 at 12:06
  

  
  
  
  

add a comment | 

Following code passed the error

# Create an array which has small value (1e-4), 
# whose shape is (2,512,512,1)
small_val=np.full((2,512,512,1),1e-4).astype("float32")

# Convert numpy array to tf.constant
small_val=tf.constant(small_val)

# Use tf.where()
intensity=tf.where(
 tf.math.abs(intensity)<1e-4,
 small_val,
 intensity)

# Error doesn't occur
print(intensity.shape)
# (2, 512, 512, 1)

share|improve this answer

edited Mar 28 at 9:22

AkshayNevrekar

6,9531212 gold badges2323 silver badges4545 bronze badges

answered Mar 28 at 9:09

YoungMin ParkYoungMin Park

30722 silver badges1111 bronze badges

# Create an array which has small value (1e-4), 
# whose shape is (2,512,512,1)
small_val=np.full((2,512,512,1),1e-4).astype("float32")

# Convert numpy array to tf.constant
small_val=tf.constant(small_val)

# Use tf.where()
intensity=tf.where(
 tf.math.abs(intensity)<1e-4,
 small_val,
 intensity)

# Error doesn't occur
print(intensity.shape)
# (2, 512, 512, 1)

share|improve this answer

edited Mar 28 at 9:22

AkshayNevrekar

6,9531212 gold badges2323 silver badges4545 bronze badges

answered Mar 28 at 9:09

YoungMin ParkYoungMin Park

30722 silver badges1111 bronze badges

edited Mar 28 at 9:22

AkshayNevrekar

6,9531212 gold badges2323 silver badges4545 bronze badges

edited Mar 28 at 9:22

AkshayNevrekar

6,9531212 gold badges2323 silver badges4545 bronze badges

answered Mar 28 at 9:09

YoungMin ParkYoungMin Park

30722 silver badges1111 bronze badges

answered Mar 28 at 9:09

YoungMin ParkYoungMin Park

30722 silver badges1111 bronze badges