Using tf.batch_scatter_add in Keras
I'm looking for a way to use tf.scatter_add with Keras batches.
Shape of outputs: (?, 1000) and shapes of indices and updates are (?, 100) each.
Try1: Using Keras tensors
vals = tf.scatter_add(outputs, indices, updates)
This throws an error:
'Tensor' object has no attribute '_lazy_read'
Try2: Tried using k.variable which should be updatable
vals = K.variable(outputs)
vals = tf.scatter_add(vals, inputs[1], inputs[2])
ValueError: initial_value must have a shape specified:
Tensor("scatter_add_43/zeros_like:0", shape=(?, 1000), dtype=float32))
Any clues? Scatter_add and batch_scatter_add result in the same errors. Will I need to write a custom layer for this? Seems like even that will run into one of the above errors.
python tensorflow keras
edited Nov 26 '18 at 7:23
barbsan
2,45131223
asked Nov 25 '18 at 18:00
N. SawantN. Sawant
111
add a comment |
I'm looking for a way to use tf.scatter_add with Keras batches.
Shape of outputs: (?, 1000) and shapes of indices and updates are (?, 100) each.
Try1: Using Keras tensors
vals = tf.scatter_add(outputs, indices, updates)
This throws an error:
'Tensor' object has no attribute '_lazy_read'
Try2: Tried using k.variable which should be updatable
vals = K.variable(outputs)
vals = tf.scatter_add(vals, inputs[1], inputs[2])
ValueError: initial_value must have a shape specified:
Tensor("scatter_add_43/zeros_like:0", shape=(?, 1000), dtype=float32))
Any clues? Scatter_add and batch_scatter_add result in the same errors. Will I need to write a custom layer for this? Seems like even that will run into one of the above errors.
python tensorflow keras
edited Nov 26 '18 at 7:23
barbsan
2,45131223
asked Nov 25 '18 at 18:00
N. SawantN. Sawant
111
add a comment |
I'm looking for a way to use tf.scatter_add with Keras batches.
Shape of outputs: (?, 1000) and shapes of indices and updates are (?, 100) each.
Try1: Using Keras tensors
vals = tf.scatter_add(outputs, indices, updates)
This throws an error:
'Tensor' object has no attribute '_lazy_read'
Try2: Tried using k.variable which should be updatable
vals = K.variable(outputs)
vals = tf.scatter_add(vals, inputs[1], inputs[2])
ValueError: initial_value must have a shape specified:
Tensor("scatter_add_43/zeros_like:0", shape=(?, 1000), dtype=float32))
Any clues? Scatter_add and batch_scatter_add result in the same errors. Will I need to write a custom layer for this? Seems like even that will run into one of the above errors.
python tensorflow keras
edited Nov 26 '18 at 7:23
barbsan
2,45131223
asked Nov 25 '18 at 18:00
N. SawantN. Sawant
111
I'm looking for a way to use tf.scatter_add with Keras batches.
Shape of outputs: (?, 1000) and shapes of indices and updates are (?, 100) each.
Try1: Using Keras tensors
vals = tf.scatter_add(outputs, indices, updates)
This throws an error:
'Tensor' object has no attribute '_lazy_read'
Try2: Tried using k.variable which should be updatable
vals = K.variable(outputs)
vals = tf.scatter_add(vals, inputs[1], inputs[2])
ValueError: initial_value must have a shape specified:
Tensor("scatter_add_43/zeros_like:0", shape=(?, 1000), dtype=float32))
Any clues? Scatter_add and batch_scatter_add result in the same errors. Will I need to write a custom layer for this? Seems like even that will run into one of the above errors.
python tensorflow keras
python tensorflow keras
edited Nov 26 '18 at 7:23
barbsan
2,45131223
asked Nov 25 '18 at 18:00
N. SawantN. Sawant
111
edited Nov 26 '18 at 7:23
barbsan
2,45131223
asked Nov 25 '18 at 18:00
N. SawantN. Sawant
111
edited Nov 26 '18 at 7:23
barbsan
2,45131223
edited Nov 26 '18 at 7:23
barbsan
2,45131223
edited Nov 26 '18 at 7:23
barbsan
2,45131223
2,45131223
asked Nov 25 '18 at 18:00
N. SawantN. Sawant
111
asked Nov 25 '18 at 18:00
N. SawantN. Sawant
111
asked Nov 25 '18 at 18:00
N. SawantN. Sawant
111
111
add a comment |
add a comment |
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