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Functions1,208 in github.com/AI4Science-WestlakeU/wdno

⨍ Functions 1,208◇ Types & classes 150↳ Endpoints 24
↓ 2 callersFunctiondownsample_dipole_2d_2x
(tensor, scaling="average")
smoke/phi/experimental.py:102
↓ 2 callersMethodfixed_range
(self, dataset, fieldnames, selection_indices=None)
smoke/phi/data/data.py:386
↓ 2 callersMethodforward
( self, x, time, cond = None, null_cond_prob = 0., focus_prese
smoke/video_diffusion_pytorch/video_diffusion_pytorch.py:485
↓ 2 callersMethodforward
( self, x, time, cond = None, null_cond_prob = 0., focus_prese
smoke/video_diffusion_pytorch/video_diffusion_pytorch_conv3d.py:487
↓ 2 callersMethodget
(self, idx)
burgers/ddpm_burgers/data_burgers_1d.py:236
↓ 2 callersMethodget_batch_count
(self)
smoke/phi/data/data.py:618
↓ 2 callersMethodget_guidance_options
(self, **kwargs)
burgers/ddpm_burgers/diffusion_1d.py:261
↓ 2 callersFunctionget_nablaJ_2dconv
(**kwargs)
burgers/eval_ddpm_burgers.py:146
↓ 2 callersFunctionget_scheduler
(scheduler)
burgers/ddpm_burgers/model_utils.py:52
↓ 2 callersMethodget_selected_slices
(self, shape)
smoke/phi/viz/plot.py:72
↓ 2 callersMethodheatmap
(self, z, library, minmax=None)
smoke/phi/viz/plot.py:177
↓ 2 callersFunctioninit_velocity_
()
smoke/dataset/evaluate_solver.py:74
↓ 2 callersMethodis_applicable
(self, values)
smoke/phi/math/base.py:16
↓ 2 callersFunctionis_list_str
(x)
smoke/video_diffusion_pytorch/video_diffusion_pytorch.py:60
↓ 2 callersFunctionis_list_str
(x)
smoke/video_diffusion_pytorch/video_diffusion_pytorch_conv3d.py:67
↓ 2 callersFunctionl1_distance_map
Calculates the shortest distance from all grid points to the nearest entry in target_mask. Neighbouring cells are separated by distance 1. All result
smoke/phi/control/distances.py:25
↓ 2 callersMethodload
(self, milestone, **kwargs)
smoke/video_diffusion_pytorch/video_diffusion_pytorch.py:953
↓ 2 callersFunctionload_burgers_dataset
(args, RESCALER)
burgers/ddpm_burgers/test_util.py:131
↓ 2 callersFunctionload_burgers_dataset_wavelet
(args, RESCALER)
burgers/ddpm_burgers/test_util.py:141
↓ 2 callersFunctionload_ddpm_base_model
(args, shape, ori_shape, RESCALER)
smoke/ddpm/utils.py:104
↓ 2 callersFunctionload_edge_flip
(fpath)
burgers/ddpm_burgers/result_io.py:93
↓ 2 callersMethodmatmul
(self, A, b)
smoke/phi/math/base.py:55
↓ 2 callersMethodmaximum
(self, a, b)
smoke/phi/math/tensorflow_backend.py:125
↓ 2 callersFunctionmetric
Evaluates the control based on the state deviation and the control cost. Note that f and u should NOT be rescaled. (Should be directly input
burgers/ddpm_burgers/test_util.py:33
↓ 2 callersMethodminimum
(self, a, b)
smoke/phi/math/tensorflow_backend.py:128
↓ 2 callersFunctionmoment_downsample2x
(tensor, sum=False)
smoke/phi/experimental.py:121
↓ 2 callersMethodmulti_evaluate
pred: torch.Tensor, [B, nt, 6, nx, nx] data: torch.Tensor, control: [B, 256, 1, 64, 64], simulation: [B, 32, 1, 128, 128]
smoke/inference_2d.py:383
↓ 2 callersMethodmulti_lookup
(self, indices)
smoke/phi/data/data.py:469
↓ 2 callersMethodneed_factor
(self, total_size, add_count)
smoke/phi/data/data.py:287
↓ 2 callersMethodp_sample
(self, x, t: int, x_self_cond=None, **kwargs)
burgers/ddpm_burgers/diffusion_1d.py:252
↓ 2 callersMethodp_sample
Different design_guidance follows the paper "Universal Guidance for Diffusion Models"
smoke/ddpm/diffusion_2d.py:770
↓ 2 callersMethodp_sample
(self, x, t, cond = None, cond_scale = 1., clip_denoised = True)
smoke/video_diffusion_pytorch/video_diffusion_pytorch.py:700
↓ 2 callersMethodp_sample
(self, x, t, cond = None, cond_scale = 1., clip_denoised = True)
smoke/video_diffusion_pytorch/video_diffusion_pytorch_conv3d.py:708
↓ 2 callersFunctionplaceholders_to_fieldnames
(placeholders)
smoke/phi/data/data.py:544
↓ 2 callersMethodplay
(self, max_steps=None, callback=None, framerate=None, allow_recording=True)
smoke/phi/model.py:300
↓ 2 callersMethodpredict_start_from_noise
(self, x_t, t, noise)
burgers/ddpm_burgers/diffusion_1d.py:172
↓ 2 callersMethodpredict_start_from_noise
(self, x_t, t, noise)
smoke/ddpm/diffusion_2d.py:689
↓ 2 callersMethodprint
(self, item, tabs=0, is_datetime=None, banner_size=0, end=None, avg_window=-1, precision="second", is_silent=F
smoke/ddpm/utils.py:169
↓ 2 callersFunctionprob_mask_like
(shape, prob, device)
smoke/video_diffusion_pytorch/video_diffusion_pytorch.py:52
↓ 2 callersFunctionprob_mask_like
(shape, prob, device)
smoke/video_diffusion_pytorch/video_diffusion_pytorch_conv3d.py:59
↓ 2 callersMethodq_sample
(self, x_start, t, noise=None)
burgers/ddpm_burgers/diffusion_1d.py:521
↓ 2 callersMethodq_sample
(self, x_start, t, noise=None)
smoke/ddpm/diffusion_2d.py:970
↓ 2 callersMethodq_sample
(self, x_start, t, noise = None)
smoke/video_diffusion_pytorch/video_diffusion_pytorch.py:749
↓ 2 callersMethodq_sample
(self, x_start, t, noise = None)
smoke/video_diffusion_pytorch/video_diffusion_pytorch_conv3d.py:757
↓ 2 callersFunctionrand_f
(is_rand_amp=True)
burgers/ddpm_burgers/generate_burgers.py:246
↓ 2 callersMethodread_array
(self, fieldname, index)
smoke/phi/fluidformat.py:145
↓ 2 callersFunctionread_sim_frames
(simpath, fieldnames=None, indices=None)
smoke/phi/fluidformat.py:52
↓ 2 callersMethodrecord_frame
(self)
smoke/phi/model.py:323
↓ 2 callersMethodreset_parameters
(self)
smoke/video_diffusion_pytorch/video_diffusion_pytorch.py:935
↓ 2 callersMethodreset_parameters
(self)
smoke/video_diffusion_pytorch/video_diffusion_pytorch_conv3d.py:943
↓ 2 callersMethodrestore_new_scope
(self, dir, saved_scope, tf_scope)
smoke/phi/tf/flow.py:181
↓ 2 callersMethodsample
Kwargs: nablaJ: a gradient function returning nablaJ for diffusion guidance. Can use the functi
burgers/ddpm_burgers/diffusion_1d.py:462
↓ 2 callersMethodsample_noise
(self, shape, device)
smoke/ddpm/diffusion_2d.py:766
↓ 2 callersMethodsave
(self, milestone)
smoke/video_diffusion_pytorch/video_diffusion_pytorch.py:944
↓ 2 callersMethodsave
(self, milestone)
smoke/video_diffusion_pytorch/video_diffusion_pytorch_conv3d.py:952
↓ 2 callersFunctionsave_edge_flip
(edge_flip, fpath)
burgers/ddpm_burgers/result_io.py:85
↓ 2 callersMethodscene_summary
(self)
smoke/phi/model.py:266
↓ 2 callersMethodshape
Returns the shape including batch dimension and component dimension of a tensor containing the given element type. This shape corresponds to the dime
smoke/phi/flow.py:201
↓ 2 callersMethodshape
(self)
smoke/phi/math/nd.py:584
↓ 2 callersFunctionsolver
Input: sim: environment of the fluid init_velocity: numpy array, [128,128,2] init_density: numpy array, [nx,nx] c
smoke/dataset/evaluate_solver.py:135
↓ 2 callersFunctionsparse_cg
(divergence, A, max_iterations, guess, accuracy, back_prop=False)
smoke/phi/solver/sparse.py:122
↓ 2 callersFunctionsparse_pressure_matrix
Builds a sparse matrix such that when applied to a flattened pressure field, it calculates the laplace of that field, taking into account obstacles a
smoke/phi/solver/sparse.py:27
↓ 2 callersFunctiontext_to_pixels
(text, size=10, binary=False, as_numpy_array=True)
smoke/phi/control/voxelutil.py:7
↓ 2 callersMethodtotal_size
(self)
smoke/phi/data/data.py:379
↓ 2 callersMethodunstack
(self, tensor, axis=0)
smoke/phi/math/base.py:110
↓ 2 callersMethodval_dict
(self, subrange=None)
smoke/phi/tf/model.py:174
↓ 2 callersMethodvalidate
(self, create_checkpoint=False)
smoke/phi/tf/model.py:148
↓ 2 callersMethodwhile_loop
(self, cond, body, loop_vars, shape_invariants=None, parallel_iterations=10, back_prop=True,
smoke/phi/math/base.py:58
↓ 1 callersFunctionCordsByRow
smoke/phi/solver/cuda/src/laplace_op.cu.cc:32
↓ 1 callersFunctionDiff_mat_1D
(Nx, device='cpu')
burgers/ddpm_burgers/generate_burgers.py:86
↓ 1 callersFunctionDownsample
(dim, dim_out = None)
burgers/ddpm_burgers/unet.py:32
↓ 1 callersFunctionDownsample
(dim)
smoke/video_diffusion_pytorch/video_diffusion_pytorch.py:149
↓ 1 callersFunctionDownsample
(dim)
smoke/video_diffusion_pytorch/video_diffusion_pytorch_conv3d.py:162
↓ 1 callersFunctionDownsample2d
(dim, dim_out = None)
burgers/ddpm_burgers/unet.py:41
↓ 1 callersFunctionLaunchPressureKernel
smoke/phi/solver/cuda/src/pressure_solve_op.cu.cc:70
↓ 1 callersFunctionNone_in
(list)
smoke/phi/data/data.py:216
↓ 1 callersFunctionUpsample
(dim, dim_out = None)
burgers/ddpm_burgers/unet.py:26
↓ 1 callersFunctionUpsample
(dim)
smoke/video_diffusion_pytorch/video_diffusion_pytorch.py:146
↓ 1 callersFunctionUpsample
(dim)
smoke/video_diffusion_pytorch/video_diffusion_pytorch_conv3d.py:159
↓ 1 callersFunctionUpsample2d
(dim, dim_out = None)
burgers/ddpm_burgers/unet.py:35
↓ 1 callersMethod__div__
(self, other)
smoke/phi/math/nd.py:571
↓ 1 callersMethod__getitem__
(self, idx)
burgers/ddpm_burgers/data_burgers_1d.py:233
↓ 1 callersMethod__init__
( self, model, *, seq_length, # define sampling size # wavelet
burgers/ddpm_burgers/diffusion_1d.py:41
↓ 1 callersMethod__init__
(self, index, density, velocity, type=TYPE_KEYFRAME)
smoke/phi/control/smoke_control.py:7
↓ 1 callersMethod__init__
(self, autodiff=False)
smoke/phi/solver/sparse.py:84
↓ 1 callersMethod__init__
(self, name)
smoke/phi/solver/base.py:11
↓ 1 callersMethod__init__
(self, flip_dimensions, field, flip_vectors=True, affect_flags=(DATAFLAG_TRAIN,))
smoke/phi/data/augment.py:47
↓ 1 callersMethod__init__
( self, # dataset, dataset_path, time_steps=256, steps=32, all
smoke/ddpm/data_2d.py:19
↓ 1 callersMethod__len__
(self)
burgers/ddpm_burgers/data_burgers_1d.py:230
↓ 1 callersMethod__mul__
(self, other)
smoke/phi/math/nd.py:562
↓ 1 callersMethod_advect_centered_field
(self, field, dt, interpolation)
smoke/phi/math/nd.py:422
↓ 1 callersFunction_all_density_valid
(density, fluid_mask)
smoke/phi/control/voxelutil.py:77
↓ 1 callersMethod_augment_interleave
(self, datasource, indices)
smoke/phi/data/augment.py:33
↓ 1 callersFunction_backward_diff_nd
(field, dims)
smoke/phi/math/nd.py:161
↓ 1 callersFunction_boundary_circular
(sample_coords, input_size)
smoke/phi/math/tensorflow_backend.py:346
↓ 1 callersMethod_centered_block_advection
(self, field, dt)
smoke/phi/math/nd.py:493
↓ 1 callersFunction_central_diff_nd
(field, dims)
smoke/phi/math/nd.py:183
↓ 1 callersFunction_central_divergence_nd
(tensor)
smoke/phi/math/nd.py:119
↓ 1 callersFunction_check_same_dimensions
(arrays)
smoke/phi/fluidformat.py:21
↓ 1 callersFunction_conv_laplace_2d
(tensor)
smoke/phi/math/nd.py:215
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