Remove softmax

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Author: sidart

backends/cortex_m/ops/operators.py

@@ -13,9 +13,6 @@
 # New operator library with a custom namespace to allow fusion etc.
 lib = Library("cortex_m", "DEF")
 
-# Import these for the cadence function signatures.
-import executorch.backends.cortex_m.cortex_m_ops_lib  # noqa: F401
-
 ###
 # add.Tensor
 ###
@@ -148,19 +145,3 @@ def dequantize_per_tensor_impl(
     return exir_ops.edge.quantized_decomposed.dequantize_per_tensor.default(
         input, scale, zero_point, quant_min, quant_max, dtype
     )
-
-lib.define(
-    "softmax(Tensor self, int dim, bool half_to_float) -> Tensor"
-)
-lib.define(
-    "softmax.out(Tensor self, int dim, bool half_to_float, *, Tensor(a!) out) -> Tensor(a!)"
-)
-@impl(lib, "softmax", "CompositeExplicitAutograd")
-def softmax_impl(self: torch.Tensor, dim: int, half_to_float: bool) -> torch.Tensor:
-    # Call your custom edge op or fallback
-    # return exir_ops.edge.cortex_m.softmax(self, dim, half_to_float)
-    # ctx = get_kernel_ctx()  # gets KernelRuntimeContext*
-    return {}
-@impl(lib, "softmax.out", "CompositeExplicitAutograd")
-def softmax_out_impl(self: torch.Tensor, dim: int, half_to_float: bool, out: torch.Tensor) -> torch.Tensor:
-    return exir_ops.edge.cortex_m.softmax_out(self, dim, half_to_float, out)

backends/cortex_m/ops/operators.yaml

@@ -28,14 +28,3 @@
     - arg_meta: null
       kernel_name: cortex_m::aten_add_tensor
 
-- func: cortex_m::softmax(Tensor self, int dim, bool half_to_float) -> Tensor
-  variants: function
-  kernels:
-    - arg_meta: null
-      kernel_name: cortex_m::softmax
-
-- func: cortex_m::softmax.out(Tensor self, int dim, bool half_to_float, *, Tensor(a!) out) -> Tensor(a!)
-  variants: function
-  kernels:
-    - arg_meta: null
-      kernel_name: cortex_m::softmax_out

backends/cortex_m/passes/replace_quant_nodes_pass.py

@@ -39,14 +39,6 @@ def __init__(self):
                 "new_target": exir_ops.edge.cortex_m.add.Tensor,
                 "qualifier": lambda args: True,
             },
-            exir_ops.edge.aten._softmax.out: {
-                "new_target": exir_ops.edge.cortex_m.softmax.out,
-                "qualifier": lambda args: True,
-            },
-            exir_ops.edge.aten._softmax.default: {
-                "new_target": exir_ops.edge.cortex_m.softmax,  # or .softmax if you have an out variant
-                "qualifier": lambda args: True,
-            },
             exir_ops.edge.quantized_decomposed.quantize_per_tensor.default: {
                 "new_target": exir_ops.edge.cortex_m.quantize_per_tensor.default,
                 "qualifier": self._is_qualified_int8_node,