↓ 1 callersFunctionget_down_block(
down_block_type,
num_layers,
in_channels,
out_channels,
temb_channels,
add_downsampl
2_charactor_reconstructor/mvdiffusion/models/unet_mv2d_blocks.py:30
↓ 1 callersFunctionget_offset_mask(vertices, faces, thin_coords, coord_dists, min_thickness, type='double')
2_charactor_reconstructor/instant_nsr/utils/thinning_utils.py:96
↓ 1 callersFunctionget_offset_mask(vertices, faces, thin_coords, coord_dists, min_thickness, type='double')
2_charactor_reconstructor/instant_nsr/utils/thin.py:86
↓ 1 callersFunctionget_up_block(
up_block_type,
num_layers,
in_channels,
out_channels,
prev_output_channel,
temb_chan
2_charactor_reconstructor/mvdiffusion/models/unet_mv2d_blocks.py:260
↓ 1 callersMethodmake_net(self, n, flt_in, flt_out=1, k=4, stride=2, bias=True)
3_style_translator/training/models.py:443
↓ 1 callersMethodprepare_latents(self, batch_size, num_channels_latents, height, width, dtype, device, generator, latents=None)
2_charactor_reconstructor/mvdiffusion/pipelines/pipeline_mvdiffusion_image.py:254
↓ 1 callersMethodresnet_block(self, in_filters, out_filters, size, stride, padding, bias,
norm_layer, nonlinearity)
3_style_translator/training/models.py:145
↓ 1 callersMethodresnet_block(self, in_filters, out_filters, size, stride, padding, bias,
norm_layer, nonlinearity)
3_style_translator/training/models.py:372
↓ 1 callersFunctionthining_processing(v, f, config, save_cache=True, theta_1=11, theta_2=9, r=11)
2_charactor_reconstructor/instant_nsr/utils/thin.py:191
↓ 1 callersFunctionthinning_processing(v, f, config, save_cache=True, theta_1=11, theta_2=6, r=11)
2_charactor_reconstructor/instant_nsr/utils/thinning_utils.py:201