remove the explicit input_shape arguments

NNPDF · Jun 18, 2024 · e5ca1ed · e5ca1ed
1 parent ec43880
commit e5ca1ed
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Showing 3 changed files with 2 additions and 8 deletions.
diff --git a/n3fit/src/n3fit/backends/keras_backend/base_layers.py b/n3fit/src/n3fit/backends/keras_backend/base_layers.py
@@ -135,7 +135,6 @@ def apply_dense(xinput):
     "dense": (
         MultiDense,
         {
-            "input_shape": (1,),
             "replica_seeds": None,
             "base_seed": 0,
             "kernel_initializer": "glorot_normal",
@@ -148,7 +147,6 @@ def apply_dense(xinput):
     "single_dense": (
         Dense,
         {
-            "input_shape": (1,),
             "kernel_initializer": "glorot_normal",
             "units": 5,
             "activation": "sigmoid",
@@ -158,7 +156,6 @@ def apply_dense(xinput):
     "dense_per_flavour": (
         dense_per_flavour,
         {
-            "input_shape": (1,),
             "kernel_initializer": "glorot_normal",
             "units": 5,
             "activation": "sigmoid",

diff --git a/n3fit/src/n3fit/model_gen.py b/n3fit/src/n3fit/model_gen.py
@@ -580,7 +580,7 @@ def pdfNN_layer_generator(
     )
 
     # Evolution layer
-    layer_evln = FkRotation(input_shape=(last_layer_nodes,), output_dim=out, name="pdf_FK_basis")
+    layer_evln = FkRotation(output_dim=out, name="pdf_FK_basis")
 
     # Normalization and sum rules
     if impose_sumrule:
@@ -593,7 +593,6 @@ def pdfNN_layer_generator(
 
     compute_preprocessing_factor = Preprocessing(
         flav_info=flav_info,
-        input_shape=(1,),
         name=PREPROCESSING_LAYER_ALL_REPLICAS,
         replica_seeds=seed,
         large_x=not subtract_one,
@@ -753,7 +752,6 @@ def layer_generator(i_layer, nodes_out, activation):
                     kernel_initializer=initializers,
                     units=int(nodes_out),
                     activation=activation,
-                    input_shape=(nodes_in,),
                     basis_size=basis_size,
                 )
                 layers.append(layer)
@@ -775,7 +773,6 @@ def layer_generator(i_layer, nodes_out, activation):
                 ),
                 units=nodes_out,
                 activation=activation,
-                input_shape=(nodes_in,),
                 regularizer=reg,
             )
 

diff --git a/n3fit/src/n3fit/msr.py b/n3fit/src/n3fit/msr.py
@@ -88,7 +88,7 @@ def generate_msr_model_and_grid(
     )([x_divided, pdf_xgrid_integration])
 
     # 4. Integrate the pdf
-    pdf_integrated = xIntegrator(weights_array, input_shape=(nx,))(pdf_integrand)
+    pdf_integrated = xIntegrator(weights_array)(pdf_integrand)
 
     # 5. THe input for the photon integral, will be set to 0 if no photons
     photon_integral = Input(shape=(replicas, 1), batch_size=1, name='photon_integral')