Use policy.dtype as the sole precision setting (Dita 2.0.1)

Remove use_amp from model config.json and publish the validated 2.0.1 runtime. The inherited LeRobot flag is derived internally from dtype. Model weights, processor files, statistics and gripper modes are unchanged.

.gitattributes

@@ -35,3 +35,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 lerobot_policy_dita-1.0.5-py3-none-any.whl filter=lfs diff=lfs merge=lfs -text
 lerobot_policy_dita-2.0.0-py3-none-any.whl filter=lfs diff=lfs merge=lfs -text
+lerobot_policy_dita-2.0.1-py3-none-any.whl filter=lfs diff=lfs merge=lfs -text

GRIPPER_MODES.md

@@ -1,6 +1,6 @@
 # DITA gripper modes
 
-Runtime **2.0.0** supports `policy.gripper_mode=binary` and `continuous`. The mode is
+Runtime **2.0.1** supports `policy.gripper_mode=binary` and `continuous`. The mode is
 saved in `config.json` and both processor JSON files. The public LeRobot processor
 factory applies the active policy mode when loading pretrained templates, including
 CLI overrides. Conflicting explicit processor modes fail. New fine-tuning binds the
@@ -8,7 +8,7 @@ target dataset statistics; resume keeps the saved statistics.
 
 The config schema replaces the serialized `action_normalization_mask` and
 `gripper_sign_flip` fields with `gripper_mode`. Old policy and processor configs are
-not supported. Use the updated Hub revisions and their 2.0.0 wheel together.
+not supported. Use the updated Hub revisions and their 2.0.1 wheel together.
 
 | Contract | `binary` | `continuous` |
 | --- | --- | --- |
@@ -40,7 +40,7 @@ all converted LIBERO inference outputs unchanged.
 Install the runtime bundled with the updated initialization:
 
 ```bash
-pip install 'lerobot_policy_dita[training] @ https://huggingface.co/albus2024/dita_droid_pretrain/resolve/main/lerobot_policy_dita-2.0.0-py3-none-any.whl'
+pip install 'lerobot_policy_dita[training] @ https://huggingface.co/albus2024/dita_droid_pretrain/resolve/main/lerobot_policy_dita-2.0.1-py3-none-any.whl'
 ```
 
 LIBERO:
@@ -120,3 +120,5 @@ saved statistics, real action encode/decode, `[4, 10, 7]` chunk inference, and
 The 2026-09-14 checks passed on three episodes of each real dataset with BF16 and
 batch size four. They validate training and inference mechanics, not convergence,
 LIBERO task success, or a physical SO101 rollout.
+
+See the [validation results](GRIPPER_VALIDATION.md) for the checked datasets and scope.

README.md

@@ -31,14 +31,14 @@ This repository is a strict LeRobot conversion of `libero_spatial.pth` from the
 - Rollout: `traj_length=11`, two-frame history, `chunk_size=10`, `n_action_steps=1`,
   `num_inference_steps=10`, DDIM `prediction_type=epsilon`, and CUDA AMP by default.
 - `policy.dtype` controls compute precision (`float32`, `float16`, `bfloat16`);
-  parameters remain FP32. Explicit precision overrides `policy.use_amp`.
+  parameters remain FP32. `dtype` is the sole precision setting; `use_amp` is derived internally.
 - LIBERO's LeRobot environment processor performs the 180° image rotation. The policy does not
   rotate the image a second time.
 
 ## Install
 
 ```bash
-pip install "lerobot_policy_dita[libero] @ https://huggingface.co/albus2024/dita_spatial/resolve/main/lerobot_policy_dita-2.0.0-py3-none-any.whl"
+pip install "lerobot_policy_dita[libero] @ https://huggingface.co/albus2024/dita_spatial/resolve/main/lerobot_policy_dita-2.0.1-py3-none-any.whl"
 ```
 
 ## Evaluate
@@ -68,7 +68,7 @@ separately before using the policy; conversion alone does not establish rollout
 ## Runtime 2.0.0 gripper contract
 
 `gripper_mode` replaces the serialized action mask and gripper sign fields. Old
-policy/processor configs are not supported. Install the 2.0.0 wheel with this
+policy/processor configs are not supported. Install the 2.0.1 wheel with this
 revision. See [gripper modes](GRIPPER_MODES.md) for training and SO101 EEF use.
 
 The four LIBERO models default to `binary`; the DROID initialization defaults to
@@ -77,8 +77,22 @@ DROID, pass `--policy.gripper_mode=binary`. Both saved processors follow that
 override. Binary labels are -1=open/+1=closed; continuous gripper uses dataset
 min/max while pose uses quantiles.
 
-The runtime validation report covers real LIBERO and SO101 training (10 steps plus
+The archived [2.0.0 validation report](history/runtime-2.0.0/runtime_validation_report.json) covers real LIBERO and SO101 training (10 steps plus
 one resumed update), offline inference, wheel verification, four LIBERO checkpoint
 action parity, and three LIBERO Spatial simulator steps. These checks do not
 establish convergence, task success, or a physical SO101 rollout. Model weights
 and existing LIBERO statistics are unchanged in this update.
+
+## Runtime 2.0.1 precision configuration
+
+`policy.dtype` is the only precision setting: `float16` (default), `bfloat16`,
+or `float32`. `null` is invalid. `use_amp` is omitted from model `config.json`;
+the inherited LeRobot runtime flag is derived from dtype and does not select
+precision. Use `--policy.dtype=float32` to disable AMP, or
+`--policy.dtype=bfloat16` for BF16 mixed precision. Parameters remain FP32.
+
+This refresh removes only `use_amp` from the model configuration and packages
+the updated runtime. Model weights, processor files, action statistics and
+existing binary/continuous gripper modes are unchanged. See
+[runtime validation](runtime_validation_report.json) for the checks run with
+2.0.1; previous validation reports are historical.

artifact_sha256.json

@@ -1,15 +1,21 @@
 {
-  "GRIPPER_MODES.md": "92373ff4adbdb04cf5d5c415b9f56c29d768111a8fa712b669d2e0fb763ea5a4",
-  "README.md": "763554f36545767380f23cc4c7faa6d94c5c107032fd9487a5cdd0c68d10f2ba",
-  "config.json": "81f167a8f27d76f65fa87d0bbe82574b0b139c27e08d5a3e78045b672b24d215",
+  "GRIPPER_MODES.md": "8abbf9d35fcaef99b2ec536fb48dd304655332d4009faf89086b59c5dafd5461",
+  "README.md": "6d260d2bba460a48aa8ad50809c9e101dfd2324ccd5ce73cf3cca87ce47a67f4",
+  "config.json": "eac9c9a6a3300f8956110320a8d1114445871b9b5e98c04cec493a74117ded27",
   "conversion_metadata.json": "178d36b3b8c55ca3e1d6479e4211825700d1b34e10562c28c640fdc4b9bb6567",
+  "history/runtime-2.0.0/runtime_metadata.json": "b36651ec1b4a239a7c642afa696350d49260035e4ea6f9c2492356abc025a276",
+  "history/runtime-2.0.0/runtime_source_manifest.json": "9da1a65a4edc8a1fe56a580fe4ace28358b42393fb8a6d0170e6bb6a2df9af04",
+  "history/runtime-2.0.0/runtime_validation_report.json": "1872e9a2560ff916960b55aa70b26f98ac328b2c1c16c7724b191bff69b81792",
+  "lerobot_policy_dita-1.0.5-py3-none-any.whl": "8e4a6c5bf9d52a636751b97237305c13454d8091a9eb900fabcac875a7ae809e",
   "lerobot_policy_dita-2.0.0-py3-none-any.whl": "b948a1e1b2f2fb22ab1f952195ccae3006e08ad3f2695825533262296395ce01",
+  "lerobot_policy_dita-2.0.1-py3-none-any.whl": "85b9d092f9b2ad072b0d53aa2b197d9694116ad5a9677ee7620dbbc1fab53854",
+  "local_verification.json": "a5a74b41390f001f6fc4e6a922358ac450bb2b8d70a68159cf7b8ec5696a7fa5",
   "model.safetensors": "eba43c4c62230b70c834142c14128b829feed93a200c6cb82d95b5599e160f87",
   "policy_postprocessor.json": "2668a59651f8fc638914065f71d7efebc48addca535891e38d75d4c2ba5e924c",
   "policy_postprocessor_step_0_dita_masked_unnormalizer_processor.safetensors": "a465763bfb581a54d47fd7f02f57bfe9a20587ac9b0ba8c51df72f89f292a9a4",
   "policy_preprocessor.json": "ead05cc569fedb9f4ad5bc1338af09cd2174a1b83ac324be56f5c48049286a01",
   "policy_preprocessor_step_4_dita_masked_normalizer_processor.safetensors": "a465763bfb581a54d47fd7f02f57bfe9a20587ac9b0ba8c51df72f89f292a9a4",
-  "runtime_metadata.json": "b36651ec1b4a239a7c642afa696350d49260035e4ea6f9c2492356abc025a276",
-  "runtime_source_manifest.json": "9da1a65a4edc8a1fe56a580fe4ace28358b42393fb8a6d0170e6bb6a2df9af04",
-  "runtime_validation_report.json": "1872e9a2560ff916960b55aa70b26f98ac328b2c1c16c7724b191bff69b81792"
+  "runtime_metadata.json": "eca09aff407cc9758a8cbfb078c4d570d06b56db9099366edcfb0503f47be815",
+  "runtime_source_manifest.json": "0960d128de0ee20e9379e83f67be8242124cf57d189633f17c426786d9c8d32e",
+  "runtime_validation_report.json": "933de31fa2d6eab4ea82fef7e4dcf197a5f73b310b41b0249db32ec8a2cc47f9"
 }

config.json

@@ -20,7 +20,6 @@
     }
   },
   "device": "cuda",
-  "use_amp": true,
   "use_peft": false,
   "push_to_hub": false,
   "repo_id": null,

history/runtime-2.0.0/runtime_metadata.json

@@ -0,0 +1,23 @@
+{
+  "updated_at_utc": "2026-09-14T10:39:26.558128+00:00",
+  "runtime_version": "2.0.0",
+  "minimum_runtime_version": "2.0.0",
+  "runtime_wheel": "lerobot_policy_dita-2.0.0-py3-none-any.whl",
+  "runtime_wheel_sha256": "b948a1e1b2f2fb22ab1f952195ccae3006e08ad3f2695825533262296395ce01",
+  "previous_hub_revision": "d61c3925dac60ca4c79e8ace348eb58dfe37d6ad",
+  "source_git_head": "7bc16687b141cdb7617e2a9dc6456e8ace1fedae",
+  "source_git_dirty": true,
+  "source_manifest": "runtime_source_manifest.json",
+  "model_sha256": "eba43c4c62230b70c834142c14128b829feed93a200c6cb82d95b5599e160f87",
+  "model_weights_changed": false,
+  "processor_configs_changed": true,
+  "processor_statistics_changed": false,
+  "processor_sha256": {
+    "policy_postprocessor.json": "2668a59651f8fc638914065f71d7efebc48addca535891e38d75d4c2ba5e924c",
+    "policy_preprocessor.json": "ead05cc569fedb9f4ad5bc1338af09cd2174a1b83ac324be56f5c48049286a01",
+    "policy_postprocessor_step_0_dita_masked_unnormalizer_processor.safetensors": "a465763bfb581a54d47fd7f02f57bfe9a20587ac9b0ba8c51df72f89f292a9a4",
+    "policy_preprocessor_step_4_dita_masked_normalizer_processor.safetensors": "a465763bfb581a54d47fd7f02f57bfe9a20587ac9b0ba8c51df72f89f292a9a4"
+  },
+  "gripper_mode": "binary",
+  "validation_report": "runtime_validation_report.json"
+}

history/runtime-2.0.0/runtime_source_manifest.json

@@ -0,0 +1,87 @@
+{
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+  "sha256": "b948a1e1b2f2fb22ab1f952195ccae3006e08ad3f2695825533262296395ce01",
+  "source_python_files": 79,
+  "all_source_files_match": true,
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     "lerobot_policy_dita/evaluation/trace.py": "a4399277a49e412589df69529d952e5931d87742f0a6dd16832d39cba113e1d3",
     "lerobot_policy_dita/policy/__init__.py": "9785f8e7279dc6760b4b7dbbe587ed6c6f467daa1dbbdf2ea095a645c1c52a57",
@@ -39,10 +39,10 @@
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     "lerobot_policy_dita/policy/approximation/ddim.py": "d32a16f85aa670bd07375ce2691498c47b9f9e700160fde12eea33e6a56f09fa",
     "lerobot_policy_dita/policy/attention.py": "3253866b5ea0bdf24a85b2047d813573e24588a4294adc9b72d01488d236909e",
-    "lerobot_policy_dita/policy/configuration_dita.py": "379bbbb0124e445d3930e527c5e8706451f6c16d76775f04fffdb97230761f3b",
+    "lerobot_policy_dita/policy/configuration_dita.py": "edc19d5e348270b9bebf22a0bc48d6dd1a56b084099544513e02c4d724f954ac",
     "lerobot_policy_dita/policy/evaluation/__init__.py": "8c0ca0bbd994637ce95307daec7647082fdb3e8e982073ab6c60ba7f9a16745f",
     "lerobot_policy_dita/policy/evaluation/adapter.py": "fdbfadfbfa13772eef20a513c74a06cda0e6cea456a4b2197cb314af42c2dbec",
-    "lerobot_policy_dita/policy/evaluation/static.py": "4517d7af032dee8ef0f73217a0dda023cc48d8fc6a39624b26c9647d71b0f169",
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     "lerobot_policy_dita/policy/modeling_dita.py": "1fb98b081deb3c47f51180e31874abdf342b2fb9e5b8d5d8d7bef5e60a0c7a1d",
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@@ -77,7 +77,7 @@
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-    "lerobot_policy_dita/scripts/calibrate_libero_dataset.py": "4102fcc33d27c4d2110612bfce5a05eb639eba397370e23628ce7cad627c3139",
+    "lerobot_policy_dita/scripts/calibrate_libero_dataset.py": "731e960fce5c9eefe48ec878cf8e86d1ccc7a1931ea4083d84ed6f2b464151b9",
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runtime_validation_report.json

@@ -1,470 +1,36 @@
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 }