mirror of
https://github.com/huggingface/lerobot.git
synced 2026-05-21 03:30:10 +00:00
add pi05
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+86
-9
@@ -30,14 +30,16 @@ def create_dummy_stats(config):
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return dummy_stats
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def test_hub_loading():
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"""Test loading model from HuggingFace hub."""
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print("=" * 60)
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print("PI0OpenPI HuggingFace Hub Loading Test")
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print("=" * 60)
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def test_hub_loading(model_id="pepijn223/pi0_base_fp32", model_name="PI0"):
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"""Test loading model from HuggingFace hub.
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# Model ID on HuggingFace hub
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model_id = "pepijn223/pi0_base_fp32" # We made sure this config matches our code and `PI0OpenPIConfig` by uploading a model with push_pi0_to_hub.py and copying that config.
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Args:
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model_id: HuggingFace model ID to load
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model_name: Display name for the model (e.g., "PI0", "PI0.5")
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"""
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print("=" * 60)
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print(f"{model_name} OpenPI HuggingFace Hub Loading Test")
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print("=" * 60)
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print(f"\nLoading model from: {model_id}")
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print("-" * 60)
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@@ -67,14 +69,45 @@ def test_hub_loading():
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# Get model info
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print("\nModel configuration:")
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print(f" - Model type: {'PI0.5' if policy.config.pi05 else 'PI0'}")
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print(f" - PaliGemma variant: {policy.config.paligemma_variant}")
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print(f" - Action expert variant: {policy.config.action_expert_variant}")
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print(f" - Action dimension: {policy.config.action_dim}")
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print(f" - State dimension: {policy.config.state_dim}")
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print(f" - Action horizon: {policy.config.action_horizon}")
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print(f" - Tokenizer max length: {policy.config.tokenizer_max_length}")
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print(f" - discrete_state_input: {policy.config.discrete_state_input}")
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print(f" - Device: {device}")
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print(f" - Dtype: {next(policy.parameters()).dtype}")
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# Check model-specific features
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if policy.config.pi05:
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print("\nPI0.5 specific features:")
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print(f" - Has time_mlp layers: {hasattr(policy.model, 'time_mlp_in')}")
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print(f" - Has state_proj: {hasattr(policy.model, 'state_proj')} (should be False)")
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print(f" - Uses AdaRMS: {policy.model.paligemma_with_expert.gemma_expert.config.use_adarms}")
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# Verify PI0.5 architecture
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assert hasattr(policy.model, "time_mlp_in"), "PI0.5 should have time_mlp_in"
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assert hasattr(policy.model, "time_mlp_out"), "PI0.5 should have time_mlp_out"
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assert not hasattr(policy.model, "state_proj"), "PI0.5 should not have state_proj"
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assert not hasattr(policy.model, "action_time_mlp_in"), "PI0.5 should not have action_time_mlp_in"
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print(" ✓ PI0.5 architecture verified")
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else:
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print("\nPI0 specific features:")
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print(f" - Has action_time_mlp layers: {hasattr(policy.model, 'action_time_mlp_in')}")
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print(f" - Has state_proj: {hasattr(policy.model, 'state_proj')} (should be True)")
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print(
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f" - Uses AdaRMS: {policy.model.paligemma_with_expert.gemma_expert.config.use_adarms} (should be False)"
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)
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# Verify PI0 architecture
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assert hasattr(policy.model, "action_time_mlp_in"), "PI0 should have action_time_mlp_in"
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assert hasattr(policy.model, "action_time_mlp_out"), "PI0 should have action_time_mlp_out"
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assert hasattr(policy.model, "state_proj"), "PI0 should have state_proj"
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assert not hasattr(policy.model, "time_mlp_in"), "PI0 should not have time_mlp_in"
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print(" ✓ PI0 architecture verified")
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except Exception as e:
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print(f"✗ Failed to load model: {e}")
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return False
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@@ -177,11 +210,55 @@ def test_hub_loading():
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return False
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print("\n" + "=" * 60)
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print("✓ All tests passed!")
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print(f"✓ All tests passed for {model_name}!")
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print("=" * 60)
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return True
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def main():
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"""Run tests for both PI0 and PI0.5 models."""
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print("\n")
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print("╔" + "═" * 58 + "╗")
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print("║" + " PI0 & PI0.5 HuggingFace Hub Loading Test Suite ".center(58) + "║")
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print("╚" + "═" * 58 + "╝")
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print()
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results = []
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# Test PI0 model
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print("\n[Test 1/2] Testing PI0 model...")
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print("─" * 60)
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pi0_success = test_hub_loading(model_id="pepijn223/pi0_base_fp32", model_name="PI0")
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results.append(("PI0", pi0_success))
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# Test PI0.5 model
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print("\n\n[Test 2/2] Testing PI0.5 model...")
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print("─" * 60)
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pi05_success = test_hub_loading(model_id="pepijn223/pi05_base_fp32", model_name="PI0.5")
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results.append(("PI0.5", pi05_success))
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# Summary
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print("\n\n")
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print("╔" + "═" * 58 + "╗")
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print("║" + " TEST SUMMARY ".center(58) + "║")
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print("╚" + "═" * 58 + "╝")
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all_passed = True
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for model_name, success in results:
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status = "✅ PASSED" if success else "❌ FAILED"
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print(f" {model_name:10} : {status}")
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if not success:
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all_passed = False
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print()
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if all_passed:
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print("🎉 All models loaded and tested successfully!")
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else:
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print("⚠️ Some tests failed. Check the output above for details.")
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return all_passed
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if __name__ == "__main__":
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success = test_hub_loading()
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success = main()
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exit(0 if success else 1)
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