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New harder task #405

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4a1f943
added new harder hypergrid variant - tests failing - with notebook a…
josephdviviano Oct 3, 2025
ace32d0
formatting
josephdviviano Oct 3, 2025
a46f6b9
added verifiable mode visualization for hypergrid
josephdviviano Oct 3, 2025
9e39720
documentation improvements, removal of magic numbers
josephdviviano Oct 3, 2025
3ca16b2
fix comments and pyright error
hyeok9855 Oct 7, 2025
8844310
fix test
hyeok9855 Oct 7, 2025
ca13536
added documentation on the hypergrid tasks
josephdviviano Oct 8, 2025
07756f7
Merge branch 'new_harder_task' of github.com:GFNOrg/torchgfn into new…
josephdviviano Oct 8, 2025
e420072
Merge pull request #402 from GFNOrg/hypergrid_refactor
josephdviviano Oct 14, 2025
cb631d7
Merge branch 'master' of github.com:GFNOrg/torchgfn into new_harder_task
josephdviviano Oct 14, 2025
b994544
fixed tests
josephdviviano Oct 14, 2025
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1,314 changes: 1,299 additions & 15 deletions src/gfn/gym/hypergrid.py
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14 changes: 9 additions & 5 deletions testing/test_environments.py
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Original file line number Diff line number Diff line change
Expand Up @@ -43,7 +43,7 @@ def test_HyperGrid_preprocessors(
ND_BATCH_SHAPE = (4, 2)
SEED = 1234

env = HyperGrid(ndim=NDIM, height=ENV_HEIGHT)
env = HyperGrid(ndim=NDIM, height=ENV_HEIGHT, validate_modes=False)

if preprocessor_name == "Identity":
preprocessor = IdentityPreprocessor(output_dim=NDIM)
Expand Down Expand Up @@ -72,7 +72,7 @@ def test_HyperGrid_fwd_step():
NDIM = 2
ENV_HEIGHT = BATCH_SIZE = 3

env = HyperGrid(ndim=NDIM, height=ENV_HEIGHT)
env = HyperGrid(ndim=NDIM, height=ENV_HEIGHT, validate_modes=False)
states = env.reset(batch_shape=BATCH_SIZE) # Instantiate a batch of initial states
assert (states.batch_shape[0], states.state_shape[0]) == (BATCH_SIZE, NDIM)

Expand Down Expand Up @@ -104,7 +104,7 @@ def test_HyperGrid_bwd_step():
SEED = 1234

# Testing the backward method from a batch of random (seeded) state.
env = HyperGrid(ndim=NDIM, height=ENV_HEIGHT)
env = HyperGrid(ndim=NDIM, height=ENV_HEIGHT, validate_modes=False)
states = env.reset(batch_shape=(NDIM, ENV_HEIGHT), random=True, seed=SEED)

passing_actions_lists = [
Expand Down Expand Up @@ -261,7 +261,7 @@ def test_states_getitem(ndim: int, env_name: str):
ND_BATCH_SHAPE = (2, 3)

if env_name == "HyperGrid":
env = HyperGrid(ndim=ndim, height=8)
env = HyperGrid(ndim=ndim, height=8, validate_modes=False)
elif env_name == "DiscreteEBM":
env = DiscreteEBM(ndim=ndim)
elif env_name == "Box":
Expand Down Expand Up @@ -298,7 +298,11 @@ def test_get_grid():
NDIM = 2

env = HyperGrid(
height=HEIGHT, ndim=NDIM, store_all_states=True, calculate_partition=True
height=HEIGHT,
ndim=NDIM,
store_all_states=True,
calculate_partition=True,
validate_modes=False,
)
all_states = env.all_states
assert all_states is not None
Expand Down
2 changes: 1 addition & 1 deletion testing/test_estimators.py
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Expand Up @@ -347,7 +347,7 @@ def test_numerical_stability_different_dtypes(dtype):
def test_discrete_policy_estimator_integration():
"""Test integration with DiscretePolicyEstimator."""
# Create a simple environment and estimator
env = HyperGrid(ndim=2, height=4)
env = HyperGrid(ndim=2, height=4, validate_modes=False)
preprocessor = KHotPreprocessor(env.height, env.ndim)
module = MLP(input_dim=preprocessor.output_dim, output_dim=env.n_actions)

Expand Down
2 changes: 1 addition & 1 deletion testing/test_gflownet.py
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Expand Up @@ -39,7 +39,7 @@ def test_trajectory_based_gflownet_generic():


def test_flow_matching_gflownet_generic():
env = HyperGrid(ndim=2)
env = HyperGrid(ndim=2, validate_modes=False)
preprocessor = KHotPreprocessor(ndim=env.ndim, height=env.height)
module = MLP(input_dim=preprocessor.output_dim, output_dim=env.n_actions)
estimator = DiscretePolicyEstimator(
Expand Down
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