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Update ternary and backward ternary pybind examples #15036

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Update ternary and backward ternary pybind examples #15036

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6cc5e54
Update ternary backward examples
mcw-anasuya Nov 14, 2024
0931506
Update ternary examples
mcw-anasuya Nov 14, 2024
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28 changes: 14 additions & 14 deletions ttnn/cpp/ttnn/operations/eltwise/ternary/ternary_pybind.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -51,10 +51,11 @@ void bind_ternary_composite_float(py::module& module, const ternary_operation_t&
Note : bfloat8_b/bfloat4_b supports only on TILE_LAYOUT

Example:
>>> tensor1 = ttnn.to_device(ttnn.from_torch(torch.tensor((1, 2), dtype=torch.bfloat16)), device)
>>> tensor2 = ttnn.to_device(ttnn.from_torch(torch.tensor((0, 1), dtype=torch.bfloat16)), device)
>>> tensor3 = ttnn.to_device(ttnn.from_torch(torch.tensor((0, 1), dtype=torch.bfloat16)), device)
>>> output = {1}(tensor1, tensor2, tensor3)
>>> value = 1.0
>>> tensor1 = ttnn.from_torch(torch.tensor([[1, 2], [3, 4]], dtype=torch.bfloat16), layout=ttnn.TILE_LAYOUT, device=device)
>>> tensor2 = ttnn.from_torch(torch.tensor([[1, 2], [3, 4]], dtype=torch.bfloat16), layout=ttnn.TILE_LAYOUT, device=device)
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>>> tensor3 = ttnn.from_torch(torch.tensor([[1, 2], [3, 4]], dtype=torch.bfloat16), layout=ttnn.TILE_LAYOUT, device=device)
>>> output = {1}(tensor1, tensor2, tensor3, value)
)doc",
operation.base_name(),
operation.python_fully_qualified_name(),
Expand Down Expand Up @@ -110,10 +111,9 @@ void bind_ternary_where(py::module& module, const ternary_operation_t& operation
Note : bfloat8_b/bfloat4_b supports only on TILE_LAYOUT
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Example:

>>> tensor1 = ttnn.to_device(ttnn.from_torch(torch.tensor((1, 2), dtype=torch.bfloat16)), device=device)
>>> tensor2 = ttnn.to_device(ttnn.from_torch(torch.tensor((0, 1), dtype=torch.bfloat16)), device=device)
>>> tensor3 = ttnn.to_device(ttnn.from_torch(torch.tensor((0, 1), dtype=torch.bfloat16)), device=device)
>>> tensor1 = ttnn.from_torch(torch.tensor([[1, 0], [1, 0]], dtype=torch.bfloat16), layout=ttnn.TILE_LAYOUT, device=device)
>>> tensor2 = ttnn.from_torch(torch.tensor([[1, 2], [3, 4]], dtype=torch.bfloat16), layout=ttnn.TILE_LAYOUT, device=device)
>>> tensor3 = ttnn.from_torch(torch.tensor([[1, 2], [3, 4]], dtype=torch.bfloat16), layout=ttnn.TILE_LAYOUT, device=device)
>>> output = {1}(tensor1, tensor2, tensor3)
)doc",
operation.base_name(),
Expand Down Expand Up @@ -217,9 +217,9 @@ void bind_ternary_lerp(py::module& module, const ternary_operation_t& operation,
Note : bfloat8_b/bfloat4_b supports only on TILE_LAYOUT

Example:
>>> tensor1 = ttnn.to_device(ttnn.from_torch(torch.tensor((1, 2), dtype=torch.bfloat16)), device)
>>> tensor2 = ttnn.to_device(ttnn.from_torch(torch.tensor((0, 1), dtype=torch.bfloat16)), device)
>>> tensor3 = ttnn.to_device(ttnn.from_torch(torch.tensor((0, 1), dtype=torch.bfloat16)), device)
>>> tensor1 = ttnn.from_torch(torch.tensor([[1, 0], [1, 0]], dtype=torch.bfloat16), layout=ttnn.TILE_LAYOUT, device=device)
>>> tensor2 = ttnn.from_torch(torch.tensor([[1, 2], [3, 4]], dtype=torch.bfloat16), layout=ttnn.TILE_LAYOUT, device=device)
>>> tensor3 = ttnn.from_torch(torch.tensor([[1, 2], [3, 4]], dtype=torch.bfloat16), layout=ttnn.TILE_LAYOUT, device=device)
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>>> output = {1}(tensor1, tensor2, tensor3/scalar)
)doc",
operation.base_name(),
Expand Down Expand Up @@ -287,9 +287,9 @@ void bind_ternary_mac(py::module& module, const ternary_operation_t& operation,
Note : bfloat8_b/bfloat4_b supports only on TILE_LAYOUT

Example:
>>> tensor1 = ttnn.to_device(ttnn.from_torch(torch.tensor((1, 2), dtype=torch.bfloat16)), device=device)
>>> tensor2 = ttnn.to_device(ttnn.from_torch(torch.tensor((0, 1), dtype=torch.bfloat16)), device=device)
>>> tensor3 = ttnn.to_device(ttnn.from_torch(torch.tensor((0, 1), dtype=torch.bfloat16)), device=device)
>>> tensor1 = ttnn.from_torch(torch.tensor([[1, 2], [3, 4]], dtype=torch.bfloat16), layout=ttnn.TILE_LAYOUT, device=device)
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>>> tensor2 = ttnn.from_torch(torch.tensor([[1, 2], [3, 4]], dtype=torch.bfloat16), layout=ttnn.TILE_LAYOUT, device=device)
>>> tensor3 = ttnn.from_torch(torch.tensor([[1, 2], [3, 4]], dtype=torch.bfloat16), layout=ttnn.TILE_LAYOUT, device=device)
>>> output = {1}(tensor1, tensor2/scalar, tensor3/scalar)
)doc",
operation.base_name(),
Expand Down
29 changes: 14 additions & 15 deletions ttnn/cpp/ttnn/operations/eltwise/ternary_backward/ternary_backward_pybind.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -43,12 +43,12 @@ void bind_ternary_backward(py::module& module, const ternary_backward_operation_
{3}

Example:

>>> grad_tensor = ttnn.to_device(ttnn.from_torch(torch.tensor((1, 2), dtype=torch.bfloat16)), device=device)
>>> tensor1 = ttnn.to_device(ttnn.from_torch(torch.tensor((1, 2), dtype=torch.bfloat16)), device=device)
>>> tensor2 = ttnn.to_device(ttnn.from_torch(torch.tensor((0, 1), dtype=torch.bfloat16)), device=device)
>>> tensor3 = ttnn.to_device(ttnn.from_torch(torch.tensor((0, 1), dtype=torch.bfloat16)), device=device)
>>> output = {1}(grad_tensor, tensor1, tensor2, tensor3, float)
>>> value = 1.0
>>> grad_tensor = ttnn.from_torch(torch.tensor([[1, 2], [3, 4]], dtype=torch.bfloat16), layout=ttnn.TILE_LAYOUT, device=device)
>>> tensor1 = ttnn.from_torch(torch.tensor([[1, 2], [3, 4]], dtype=torch.bfloat16, requires_grad=True), layout=ttnn.TILE_LAYOUT, device=device)
>>> tensor2 = ttnn.from_torch(torch.tensor([[1, 2], [3, 4]], dtype=torch.bfloat16, requires_grad=True), layout=ttnn.TILE_LAYOUT, device=device)
>>> tensor3 = ttnn.from_torch(torch.tensor([[1, 2], [3, 4]], dtype=torch.bfloat16, requires_grad=True), layout=ttnn.TILE_LAYOUT, device=device)
>>> output = {1}(grad_tensor, tensor1, tensor2, tensor3, value)
)doc",
operation.base_name(),
operation.python_fully_qualified_name(),
Expand Down Expand Up @@ -110,10 +110,10 @@ void bind_ternary_backward_op(py::module& module, const ternary_backward_operati


Example:
>>> grad_tensor = ttnn.to_device(ttnn.from_torch(torch.tensor((1, 2), dtype=torch.bfloat16)), device=device)
>>> tensor1 = ttnn.to_device(ttnn.from_torch(torch.tensor((1, 2), dtype=torch.bfloat16)), device=device)
>>> tensor2 = ttnn.to_device(ttnn.from_torch(torch.tensor((0, 1), dtype=torch.bfloat16)), device=device)
>>> tensor3 = ttnn.to_device(ttnn.from_torch(torch.tensor((0, 1), dtype=torch.bfloat16)), device=device)
>>> grad_tensor = ttnn.from_torch(torch.tensor([[1, 2], [3, 4]], dtype=torch.bfloat16), layout=ttnn.TILE_LAYOUT, device=device)
>>> tensor1 = ttnn.from_torch(torch.tensor([[1, 2], [3, 4]], dtype=torch.bfloat16, requires_grad=True), layout=ttnn.TILE_LAYOUT, device=device)
>>> tensor2 = ttnn.from_torch(torch.tensor([[1, 2], [3, 4]], dtype=torch.bfloat16, requires_grad=True), layout=ttnn.TILE_LAYOUT, device=device)
>>> tensor3 = ttnn.from_torch(torch.tensor([[1, 2], [3, 4]], dtype=torch.bfloat16, requires_grad=True), layout=ttnn.TILE_LAYOUT, device=device)
>>> output = {1}(grad_tensor, tensor1, tensor2, tensor3/scalar)

)doc",
Expand Down Expand Up @@ -188,11 +188,10 @@ void bind_ternary_backward_optional_output(py::module& module, const ternary_bac
{3}

Example:

>>> grad_tensor = ttnn.to_device(ttnn.from_torch(torch.tensor((1, 2), dtype=torch.bfloat16)), device=device)
>>> tensor1 = ttnn.to_device(ttnn.from_torch(torch.tensor((1, 2), dtype=torch.bfloat16)), device=device)
>>> tensor2 = ttnn.to_device(ttnn.from_torch(torch.tensor((0, 1), dtype=torch.bfloat16)), device=device)
>>> tensor3 = ttnn.to_device(ttnn.from_torch(torch.tensor((0, 1), dtype=torch.bfloat16)), device=device)
>>> grad_tensor = ttnn.from_torch(torch.tensor([[1, 2], [3, 4]], dtype=torch.bfloat16), layout=ttnn.TILE_LAYOUT, device=device)
>>> tensor1 = ttnn.from_torch(torch.tensor([[1, 0], [1, 0]], dtype=torch.bfloat16, requires_grad=True), layout=ttnn.TILE_LAYOUT, device=device)
>>> tensor2 = ttnn.from_torch(torch.tensor([[1, 2], [3, 4]], dtype=torch.bfloat16, requires_grad=True), layout=ttnn.TILE_LAYOUT, device=device)
>>> tensor3 = ttnn.from_torch(torch.tensor([[1, 2], [3, 4]], dtype=torch.bfloat16, requires_grad=True), layout=ttnn.TILE_LAYOUT, device=device)
>>> output = {1}(grad_tensor, tensor1, tensor2, tensor3)
)doc",
operation.base_name(),
Expand Down
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