Fix TF 2.20 compatibility: enforce keyword-only non-tensor args in Keras layer call methods

[Copilot]

• Fix SharedMLP.call in randlanet.py - make training keyword-only
• Fix LocalSpatialEncoding.call in randlanet.py - make training and relative_features keyword-only
• Fix AttentivePooling.call in randlanet.py - make training keyword-only
• Fix LocalFeatureAggregation.call in randlanet.py - make training keyword-only
• Fix BatchNormBlock.call call sites in network_blocks.py - pass training as keyword
• Fix UnaryBlock.call in network_blocks.py - make batch and training keyword-only
• Fix SimpleBlock.call in network_blocks.py - make batch keyword-only; fix internal training calls
• Fix ResnetBottleneckBlock.call in network_blocks.py - make batch keyword-only; fix all internal training/batch calls
• Fix NearestUpsampleBlock.call in network_blocks.py - make batch keyword-only
• Fix KPFCNN.call in kpconv.py - pass batch as keyword in all block calls; fix head_mlp/head_softmax calls
• Fix PointPillarsScatter.call in point_pillars.py - make batch_size keyword-only; fix call site in extract_feats
• Fix tf_batch_neighbors in kpconv.py - pass radius, points_row_splits, queries_row_splits as keywords to FixedRadiusSearch
• Fix SECONDFPN in point_pillars.py - add Permute layers to convert NCHW↔NHWC around Conv2DTranspose/Conv2D to avoid channels_first unsupported on CPU

Original prompt

Update the codebase to resolve errors caused by TensorFlow 2.20's stricter API for argument passing in model and layer call methods. Specifically:

• Refactor all custom Keras model and layer call methods (e.g., PointPillars, RandLANet, SharedMLP, KPConv) so that only the input tensor is accepted as a positional argument and all other arguments (like training, floats, ints, etc.) are keyword-only.
• Audit all calls to layers/models (including Sequential) to ensure additional arguments are always passed via keywords, never positionally.
• Update relevant tests (such as tests/test_models.py) to ensure model/layer calls use keyword arguments for parameters other than the primary input.
• Verify the fixes by ensuring failing tests (test_pointpillars_tf, test_randlanet_tf, test_kpconv_tf) pass, specifically eliminating errors like: Only input tensors may be passed as positional arguments, and Layers added to a Sequential model can only have a single positional argument.

Apply these changes consistently throughout the codebase to restore full TensorFlow 2.20+ compatibility.

This pull request was created from Copilot chat.

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[ssheorey]

@copilot Check CI error and fix.

[Copilot]

@copilot Check CI error and fix.

Fixed in commit 02c2dc9. Two CI failures were addressed:

1. test_kpconv_tf: In tf_batch_neighbors, FixedRadiusSearch was called with r=0.15 (float) as a positional argument. Fixed by using keyword arguments: nns(points, queries, radius=r, points_row_splits=p_splits, queries_row_splits=q_splits).

2. test_pointpillars_tf: SECONDFPN used Conv2DTranspose with data_format='channels_first' which is not supported on CPU in TF 2.20. Fixed by adding Permute((2,3,1)) (NCHW→NHWC) before and Permute((3,1,2)) (NHWC→NCHW) after each deblock's convolution, and changing the convolutions to data_format='channels_last'.