Update the API of registering fake kernels to new standard (#5084)

Summary:
Pull Request resolved: #5084

Update the decorator functions in registering operator abstract implementations/fake tensors to newer API

Reviewed By: zonglinpeng, hsharma35

Differential Revision: D62206602

Author: Yi Li

backends/cadence/aot/ops_registrations.py

@@ -11,7 +11,7 @@
 
 import torch
 from executorch.exir.scalar_type import ScalarType
-from torch.library import impl, Library
+from torch.library import Library, register_fake
 
 from .utils import get_conv1d_output_size, get_conv2d_output_size
 
@@ -69,7 +69,7 @@
 m = Library("cadence", "IMPL", "Meta")
 
 
-@impl(m, "quantize_per_tensor")
+@register_fake("cadence::quantize_per_tensor")
 def quantize_per_tensor_meta(
     input: torch.Tensor,
     scale: float,
@@ -81,7 +81,7 @@ def quantize_per_tensor_meta(
     return input.new_empty(input.size(), dtype=dtype)
 
 
-@impl(m, "dequantize_per_tensor")
+@register_fake("cadence::dequantize_per_tensor")
 def dequantize_per_tensor_meta(
     input: torch.Tensor,
     scale: float,
@@ -93,7 +93,7 @@ def dequantize_per_tensor_meta(
     return input.new_empty(input.size(), dtype=torch.float)
 
 
-@impl(m, "quantized_linear")
+@register_fake("cadence::quantized_linear")
 def quantized_linear_meta(
     src: torch.Tensor,
     weight: torch.Tensor,
@@ -115,7 +115,7 @@ def quantized_linear_meta(
     return src.new_empty(out_size, dtype=torch.uint8)
 
 
-@impl(m, "quantized_conv")
+@register_fake("cadence::quantized_conv")
 def quantized_conv_meta(
     input: torch.Tensor,
     weight: torch.Tensor,
@@ -153,7 +153,7 @@ def quantized_conv_meta(
     return input.new_empty(output_size, dtype=input.dtype)
 
 
-@impl(m, "quantized_layer_norm")
+@register_fake("cadence::quantized_layer_norm")
 def quantized_layer_norm_meta(
     input: torch.Tensor,
     X_scale: torch.Tensor,
@@ -168,7 +168,7 @@ def quantized_layer_norm_meta(
     return input.new_empty(input.size(), dtype=torch.uint8)
 
 
-@impl(m, "quantized_relu")
+@register_fake("cadence::quantized_relu")
 def quantized_relu_meta(
     X: torch.Tensor,
     X_zero_point: torch.Tensor,
@@ -179,7 +179,7 @@ def quantized_relu_meta(
     return X.new_empty(X.size(), dtype=torch.uint8)
 
 
-@impl(m, "quantized_matmul")
+@register_fake("cadence::quantized_matmul")
 def quantized_matmul_meta(
     X: torch.Tensor,
     X_zero_point: int,