From 4e0a920ea106afc36a03158b4f1a8f5a70a8e39c Mon Sep 17 00:00:00 2001
From: james77777778 <20734616+james77777778@users.noreply.github.com>
Date: Wed, 24 Apr 2024 11:53:10 +0800
Subject: [PATCH] Clean up duplicated `inputs_quantizer` (#19604)

* Cleanup duplicated `inputs_quantizer` and add type check for `input_spec` and `supports_masking`

* Revert setter
---
 keras/src/layers/core/dense.py        | 2 --
 keras/src/layers/core/einsum_dense.py | 4 ----
 2 files changed, 6 deletions(-)

diff --git a/keras/src/layers/core/dense.py b/keras/src/layers/core/dense.py
index da32e0107..8b78a2851 100644
--- a/keras/src/layers/core/dense.py
+++ b/keras/src/layers/core/dense.py
@@ -557,8 +557,6 @@ class Dense(Layer):
 
         self._tracker.unlock()
         if mode == "int8":
-            # Configure `self.inputs_quantizer`
-            self.inputs_quantizer = quantizers.AbsMaxQuantizer(axis=-1)
             # Quantize `self._kernel` to int8 and compute corresponding scale
             kernel_value, kernel_scale = quantizers.abs_max_quantize(
                 self._kernel, axis=0
diff --git a/keras/src/layers/core/einsum_dense.py b/keras/src/layers/core/einsum_dense.py
index bfc7eff43..a884171de 100644
--- a/keras/src/layers/core/einsum_dense.py
+++ b/keras/src/layers/core/einsum_dense.py
@@ -684,10 +684,6 @@ class EinsumDense(Layer):
                 self._custom_gradient_equation,
                 self._kernel_reverse_transpose_axes,
             ) = _analyze_quantization_info(self.equation, self.input_spec.ndim)
-            # Configure `self.inputs_quantizer`
-            self.inputs_quantizer = quantizers.AbsMaxQuantizer(
-                axis=self._input_reduced_axes
-            )
             # Quantize `self._kernel` to int8 and compute corresponding scale
             kernel_value, kernel_scale = quantizers.abs_max_quantize(
                 self._kernel, axis=self._kernel_reduced_axes