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Support for more TensorScatter* operations #2179

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merged 5 commits into from
May 29, 2023
Merged

Support for more TensorScatter* operations #2179

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2e9d2cc
Support for more TensorScatter* operations
javidcf May 24, 2023
57c1bf2
Fix version for tf.tensor_scatter_nd[min|max] test
javidcf May 26, 2023
bdcbb81
Removed already covered test cases
javidcf May 26, 2023
8cfbafa
Added int64 tests for tf.tensor_scatter_nd_* ops
javidcf May 26, 2023
ffb986b
Fixed line too long in tests
javidcf May 26, 2023
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3 changes: 3 additions & 0 deletions support_status.md
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Original file line number Diff line number Diff line change
Expand Up @@ -254,6 +254,9 @@
| TensorListSetItem | 7 ~ 17 |
| TensorListStack | 7 ~ 17 |
| TensorScatterAdd | 16 ~ 17 |
| TensorScatterMax | 16 ~ 17 |
| TensorScatterMin | 16 ~ 17 |
| TensorScatterSub | 16 ~ 17 |
| TensorScatterUpdate | 11 ~ 17 |
| Tile | 1 ~ 17 |
| TopKV2 | 1 ~ 17 |
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45 changes: 45 additions & 0 deletions tests/test_backend.py
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Expand Up @@ -6102,5 +6102,50 @@ def func(x):
x_val = make_xval([2, 3])
self._run_test_case(func, [_OUTPUT], {_INPUT: x_val})

@check_tf_min_version("2.3.0")
@check_opset_min_version(16, "ScatterND")
@skip_tfjs("not supported in tfjs")
def test_tensor_scatter_max(self):
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def func(tensor, indices, updates):
op = tf.tensor_scatter_nd_max(tensor, indices, updates)
return tf.identity(op, name=_TFOUTPUT)

tensor_val = make_xval([3, 4, 5])
indices_val = np.array([[2, 3], [0, 1]], np.int32)
indices64_val = indices_val.astype(np.int64)
updates_val = make_xval([2, 5]) + 3
self._run_test_case(func, [_OUTPUT], {_INPUT: tensor_val, _INPUT1: indices_val, _INPUT2: updates_val})
self._run_test_case(func, [_OUTPUT], {_INPUT: tensor_val, _INPUT1: indices64_val, _INPUT2: updates_val})

@check_tf_min_version("2.3.0")
@check_opset_min_version(16, "ScatterND")
@skip_tfjs("not supported in tfjs")
def test_tensor_scatter_min(self):
def func(tensor, indices, updates):
op = tf.tensor_scatter_nd_min(tensor, indices, updates)
return tf.identity(op, name=_TFOUTPUT)

tensor_val = make_xval([3, 4, 5])
indices_val = np.array([[2, 3], [0, 1]], np.int32)
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indices64_val = indices_val.astype(np.int64)
updates_val = make_xval([2, 5]) + 3
self._run_test_case(func, [_OUTPUT], {_INPUT: tensor_val, _INPUT1: indices_val, _INPUT2: updates_val})
self._run_test_case(func, [_OUTPUT], {_INPUT: tensor_val, _INPUT1: indices64_val, _INPUT2: updates_val})

@check_tf_min_version("1.12.1")
@check_opset_min_version(16, "ScatterND")
@skip_tfjs("not supported in tfjs")
def test_tensor_scatter_sub(self):
def func(tensor, indices, updates):
op = tf.tensor_scatter_nd_sub(tensor, indices, updates)
return tf.identity(op, name=_TFOUTPUT)

tensor_val = make_xval([3, 4, 5])
indices_val = np.array([[2, 3], [0, 1]], np.int32)
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indices64_val = indices_val.astype(np.int64)
updates_val = make_xval([2, 5]) + 3
self._run_test_case(func, [_OUTPUT], {_INPUT: tensor_val, _INPUT1: indices_val, _INPUT2: updates_val})
self._run_test_case(func, [_OUTPUT], {_INPUT: tensor_val, _INPUT1: indices64_val, _INPUT2: updates_val})

if __name__ == '__main__':
unittest_main()
31 changes: 31 additions & 0 deletions tf2onnx/onnx_opset/tensor.py
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Expand Up @@ -670,6 +670,37 @@ def version_16(cls, ctx, node, **kwargs):
node.set_attr("reduction", 'add')


@tf_op("TensorScatterMax", onnx_op="ScatterND")
class TensorScatterMax:
@classmethod
def version_16(cls, ctx, node, **kwargs):
# indices input must be int64 in ONNX.
if ctx.get_dtype(node.input[1]) != TensorProto.INT64:
ctx.insert_new_node_on_input(node, "Cast", node.input[1], to=TensorProto.INT64)
node.set_attr("reduction", 'max')


@tf_op("TensorScatterMin", onnx_op="ScatterND")
class TensorScatterMin:
@classmethod
def version_16(cls, ctx, node, **kwargs):
# indices input must be int64 in ONNX.
if ctx.get_dtype(node.input[1]) != TensorProto.INT64:
ctx.insert_new_node_on_input(node, "Cast", node.input[1], to=TensorProto.INT64)
node.set_attr("reduction", 'min')


@tf_op("TensorScatterSub", onnx_op="ScatterND")
class TensorScatterSub:
@classmethod
def version_16(cls, ctx, node, **kwargs):
# indices input must be int64 in ONNX.
if ctx.get_dtype(node.input[1]) != TensorProto.INT64:
ctx.insert_new_node_on_input(node, "Cast", node.input[1], to=TensorProto.INT64)
ctx.insert_new_node_on_input(node, "Neg", node.input[2])
node.set_attr("reduction", 'add')


@tf_op("TensorScatterUpdate", onnx_op="ScatterND")
class TensorScatterUpdate:
@classmethod
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