From 13ad46bcf02020ece23ac2db81cf73108b5af42a Mon Sep 17 00:00:00 2001 From: terrance Date: Mon, 5 Jun 2023 21:30:15 +0000 Subject: [PATCH] lint --- nerfstudio/fields/dreamfusion_field.py | 49 -------------------------- 1 file changed, 49 deletions(-) diff --git a/nerfstudio/fields/dreamfusion_field.py b/nerfstudio/fields/dreamfusion_field.py index bc7cb9136..2746d55f5 100644 --- a/nerfstudio/fields/dreamfusion_field.py +++ b/nerfstudio/fields/dreamfusion_field.py @@ -33,12 +33,6 @@ from nerfstudio.field_components.field_heads import FieldHeadNames from nerfstudio.field_components.encodings import HashEncoding, SHEncoding from nerfstudio.fields.base_field import Field -try: - pass -except ImportError: - # tinycudann module doesn't exist - pass - def get_normalized_directions(directions: Float[Tensor, "bs 3"]): """SH encoding must be in the range [0, 1] @@ -110,38 +104,6 @@ class DreamFusionField(Field): ) self.mlp_base = torch.nn.Sequential(encoder, network) - # self.mlp_base = tcnn.NetworkWithInputEncoding( - # n_input_dims=3, - # n_output_dims=1 + self.geo_feat_dim, - # encoding_config={ - # "otype": "HashGrid", - # "n_levels": num_levels, - # "n_features_per_level": features_per_level, - # "log2_hashmap_size": log2_hashmap_size, - # "base_resolution": base_res, - # "per_level_scale": growth_factor, - # }, - # network_config={ - # "otype": "FullyFusedMLP", - # "activation": "ReLU", - # "output_activation": "None", - # "n_neurons": hidden_dim, - # "n_hidden_layers": num_layers - 1, - # }, - # ) - - # self.mlp_background_color = tcnn.Network( - # n_input_dims=self.direction_encoding.n_output_dims, - # n_output_dims=3, - # network_config={ - # "otype": "FullyFusedMLP", - # "activation": "ReLU", - # "output_activation": "Sigmoid", - # "n_neurons": 32, - # "n_hidden_layers": 1, - # }, - # ) - self.mlp_background_color = MLP( in_dim=self.direction_encoding.get_out_dim(), num_layers=2, @@ -161,17 +123,6 @@ class DreamFusionField(Field): out_activation=nn.Sigmoid(), implementation=implementation, ) - # self.mlp_head = tcnn.Network( - # n_input_dims=self.geo_feat_dim, - # n_output_dims=3, - # network_config={ - # "otype": "FullyFusedMLP", - # "activation": "ReLU", - # "output_activation": "Sigmoid", - # "n_neurons": hidden_dim_color, - # "n_hidden_layers": num_layers_color - 1, - # }, - # ) def get_density(self, ray_samples: RaySamples) -> Tuple[Tensor, Tensor]: """Computes and returns the densities."""