Split bins into num_bins and bin_boundaries arguments for discretization

Rather than overload a single argument by type (with different implications for adapt), we will split out a num_bins argument for the adapt use case. This matches the argument name in other preprocessing layers (e.g. Hashing). PiperOrigin-RevId: 362167274
itrushkin · Mar 11, 2021 · bcd8b23 · bcd8b23
1 parent 02dbfed
commit bcd8b23
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diff --git a/keras/api/golden/v1/tensorflow.keras.layers.experimental.preprocessing.-discretization.pbtxt b/keras/api/golden/v1/tensorflow.keras.layers.experimental.preprocessing.-discretization.pbtxt
@@ -143,7 +143,7 @@ tf_class {
   }
   member_method {
     name: "__init__"
-    argspec: "args=[\'self\', \'bins\', \'epsilon\'], varargs=None, keywords=kwargs, defaults=[\'0.01\'], "
+    argspec: "args=[\'self\', \'bin_boundaries\', \'num_bins\', \'epsilon\'], varargs=None, keywords=kwargs, defaults=[\'None\', \'None\', \'0.01\'], "
   }
   member_method {
     name: "adapt"

diff --git a/keras/api/golden/v2/tensorflow.keras.layers.experimental.preprocessing.-discretization.pbtxt b/keras/api/golden/v2/tensorflow.keras.layers.experimental.preprocessing.-discretization.pbtxt
@@ -143,7 +143,7 @@ tf_class {
   }
   member_method {
     name: "__init__"
-    argspec: "args=[\'self\', \'bins\', \'epsilon\'], varargs=None, keywords=kwargs, defaults=[\'0.01\'], "
+    argspec: "args=[\'self\', \'bin_boundaries\', \'num_bins\', \'epsilon\'], varargs=None, keywords=kwargs, defaults=[\'None\', \'None\', \'0.01\'], "
   }
   member_method {
     name: "adapt"