Add SimVP model computational graph

[easyeasydev]

Description of changes:

This PR is to add the computational graph of the SimVP model.

Related Issues:

Linked Issues:

• Issue #

Issues closed by this PR:

• Closes #

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This change is 

[codecov]

Codecov Report

Attention: Patch coverage is 79.27928% with 23 lines in your changes missing coverage. Please review.

Project coverage is 78.00%. Comparing base (1d5140d) to head (ccc8b2c).

Files with missing lines	Patch %	Lines
lib/models/src/models/simvp/simvp.cc	77.22%	23 Missing ⚠️

Additional details and impacted files

@@                Coverage Diff                @@
##           repo-refactor    #1549      +/-   ##
=================================================
- Coverage          78.16%   78.00%   -0.16%     
=================================================
  Files                860      862       +2     
  Lines              27994    28299     +305     
  Branches             770      775       +5     
=================================================
+ Hits               21881    22076     +195     
- Misses              6113     6223     +110     

Flag	Coverage Δ
unittests	78.00% <79.27%> (-0.16%)	⬇️

Flags with carried forward coverage won't be shown. Click here to find out more.

Files with missing lines	Coverage Δ
lib/models/test/src/models/simvp/simvp.cc	100.00% <100.00%> (ø)
lib/models/src/models/simvp/simvp.cc	77.22% <77.22%> (ø)

... and 113 files with indirect coverage changes

[lockshaw]

Have you double checked the model using the model viewer to make sure everything looks as expected?

Also, there need to be a lot more comments/links referencing the original code--the goal with these is to make it trivial for someone else a year or two in the future to look through the code without you and easily double check everything against the reference implementation without having to track a whole bunch of stuff down. Ideally also some assertions on tensor shapes.

Reviewed 5 of 5 files at r1, all commit messages.
Reviewable status: all files reviewed, 21 unresolved discussions (waiting on @easyeasydev and @reyna-abhyankar)

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lib/models/src/models/simvp/simvp.cc line 24 at r1 (raw file):

std::vector<bool> create_simvp_samplings(size_t N_S, bool reverse) {
  size_t N_S_even_floor = (N_S / 2) * 2;

Pull out a separate function named round_down_to_nearest_even to improve readbility

Code quote:

 size_t N_S_even_floor = (N_S / 2) * 2;

---

lib/models/src/models/simvp/simvp.cc line 26 at r1 (raw file):

  size_t N_S_even_floor = (N_S / 2) * 2;

  auto const change_to_true = [&](size_t idx) -> bool {

Is this actually the name used in the reference implementation? It seems rather weird.

Code quote:

change_to_true

---

lib/models/src/models/simvp/simvp.cc line 37 at r1 (raw file):

  }

  return samplings;

In all of these PRs use functions from utils/containers more frequently to improve readbility.

Suggestion:

  return transform(range(N_S_even_floor), change_to_true);

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lib/models/src/models/simvp/simvp.cc line 43 at r1 (raw file):

                                  SimVPConfig const &config,
                                  tensor_guid_t const &input,
                                  size_t in_dim,

Prefer int over size_t

---

lib/models/src/models/simvp/simvp.cc line 68 at r1 (raw file):

                         SimVPConfig const &config,
                         tensor_guid_t const &input) {
  size_t C = config.in_shape.at(1); // Channel

It seems like in_shape has a fixed number of dimension, so it would probably be better to use four named fields (or even an additional struct) rather than a vector

Code quote:

  size_t C = config.in_shape.at(1); // Channel

---

lib/models/src/models/simvp/simvp.cc line 81 at r1 (raw file):

  tensor_guid_t latent = enc1;

  for (size_t i = 1; i < samplings.size(); i++) {

Suggestion:

  for (int sampling : subvec(samplings, 1, std::nullopt)) {

---

lib/models/src/models/simvp/simvp.cc line 88 at r1 (raw file):

                                 config.hid_S,
                                 config.spatio_kernel_enc,
                                 samplings[i],

Suggestion:

                                 samplings.at(i)

---

lib/models/src/models/simvp/simvp.cc line 105 at r1 (raw file):

                                        float drop_path,
                                        float init_value) {
  return input;

Seems to be missing an actual implementation?

---

lib/models/src/models/simvp/simvp.cc line 134 at r1 (raw file):

                                      float drop,
                                      float drop_path) {
  if (config.model_type != "gSTA") {

Prefer an dtgen enum instead of a string for the model type

---

lib/models/src/models/simvp/simvp.cc line 147 at r1 (raw file):

  // Downsample
  z = create_simvp_gsta_meta_block(
      cgb, config, z, channel_in, channel_hid, mlp_ratio, drop, drop_path);

Add argument name comments for all invocations of these many-argument functions for readability

Suggestion:

  z = create_simvp_gsta_meta_block(
      /*cgb=*/cgb, 
      /*config=*/config, 
      /*input=*/z, 
      /*in_channels=*/channel_in, 
      /*out_channels=*/channel_hid, 
      /*mlp_ratio=*/mlp_ratio, 
      /*drop=*/drop, 
      /*drop_path=*/drop_path);

---

lib/models/src/models/simvp/simvp.cc line 150 at r1 (raw file):

  // Middle layers
  for (size_t i = 1; i < config.N_T - 1; i++) {

Suggestion:

  for (int i : range(1, config.N_T - 1)) {

---

lib/models/src/models/simvp/simvp.cc line 153 at r1 (raw file):

    z = create_simvp_gsta_meta_block(
        cgb, config, z, channel_hid, channel_hid, mlp_ratio, drop, drop_path);
  }

Considering that this f(f(f(f(...f(x_0)...)))) pattern keeps showing up in model definitions, it might be nice to pull it out into a separate function in utils/containers named something like "primitive_recurse" or "recurse_n" or something. Thoughts? I'm sure @Marsella8 would be happy to add such a function

Code quote:

  for (size_t i = 1; i < config.N_T - 1; i++) {
    z = create_simvp_gsta_meta_block(
        cgb, config, z, channel_hid, channel_hid, mlp_ratio, drop, drop_path);
  }

---

lib/models/src/models/simvp/simvp.cc line 168 at r1 (raw file):

  std::cout << "hid shape: " << cgb.get_shape(hid) << std::endl;
  std::cout << "skip shape: " << cgb.get_shape(skip) << std::endl;

Remove prints.

Also, I assume if you were looking at the shapes then you know what they should be, so you should add in asserts on the tensor shapes where possible to improve readability and reduce the possibility of bugs

Code quote:

  std::cout << "hid shape: " << cgb.get_shape(hid) << std::endl;
  std::cout << "skip shape: " << cgb.get_shape(skip) << std::endl;

---

lib/models/src/models/simvp/simvp.cc line 174 at r1 (raw file):

  tensor_guid_t latent = hid;
  for (size_t i = 0; i < samplings.size() - 1; i++) {

Suggestion:

 for (bool sampling : subvec(samplings, 1, std::nullopt)) {

---

lib/models/src/models/simvp/simvp.cc line 192 at r1 (raw file):

                                          config.spatio_kernel_dec,
                                          false,
                                          samplings[samplings.size() - 1]);

Suggestion:

                                          samplings.back());

---

lib/models/src/models/simvp/simvp.cc line 207 at r1 (raw file):

  size_t W = config.in_shape.at(3); // Width

  // std::cout << "B T C H W: " << B << " " << T << " " << C << " " << H << " "

Remove prints

---

lib/models/src/models/simvp/simvp.cc line 219 at r1 (raw file):

  auto [embed, skip] = create_simvp_encoder(cgb, config, input);

  // std::cout << "embed shape: " << cgb.get_shape(embed) << std::endl;

Remove prints, add assertions on shape

---

lib/models/src/models/simvp/simvp.cc line 232 at r1 (raw file):

                                              config.drop_path);

  // TODO: need to reshape hid here

What's the plan for all of these TODOs? Are you waiting on something else to be implemented?

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lib/models/include/models/simvp/simvp_config.struct.toml line 28 at r1 (raw file):

[[fields]]
name = "batch_size"
type = "size_t"

Prefer int over size_t

---

lib/models/include/models/simvp/simvp_config.struct.toml line 43 at r1 (raw file):

[[fields]]
name = "N_T"

Let's keep variable names lower-case

Suggestion:

name = "n_t"

---

lib/models/include/models/simvp/simvp.h line 18 at r1 (raw file):

std::vector<bool> create_simvp_samplings(size_t N_S, bool reverse = false);

tensor_guid_t create_simvp_convsc(ComputationGraphBuilder &cgb,

Would be nice to have links here in the docstrings to wherever the equivalent code in OpenSTL is for each of these functions

[Marsella8]

Reviewable status: all files reviewed, 21 unresolved discussions (waiting on @easyeasydev, @lockshaw, and @reyna-abhyankar)

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lib/models/src/models/simvp/simvp.cc line 153 at r1 (raw file):

Previously, lockshaw (Colin Unger) wrote…

Considering that this f(f(f(f(...f(x_0)...)))) pattern keeps showing up in model definitions, it might be nice to pull it out into a separate function in utils/containers named something like "primitive_recurse" or "recurse_n" or something. Thoughts? I'm sure @Marsella8 would be happy to add such a function

See #1563