Upload folder using huggingface_hub

.gitattributes

@@ -33,3 +33,9 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+results_step-034500-epoch-08-loss=0.1167_1/log/log3.log filter=lfs diff=lfs merge=lfs -text
+results_step-034500-epoch-08-loss=0.1167_1/log/log7.log filter=lfs diff=lfs merge=lfs -text
+results_step-034500-epoch-08-loss=0.1167_2/log/log3.log filter=lfs diff=lfs merge=lfs -text
+results_step-034500-epoch-08-loss=0.1167_2/log/log7.log filter=lfs diff=lfs merge=lfs -text
+results_step-034500-epoch-08-loss=0.1167_3/log/log3.log filter=lfs diff=lfs merge=lfs -text
+results_step-034500-epoch-08-loss=0.1167_3/log/log7.log filter=lfs diff=lfs merge=lfs -text

checkpoints/pretrained_action_adapter/README.md

@@ -0,0 +1,202 @@
+---
+base_model: ./pretrained/Qwen2_5-1_5B-Instruct
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.15.2

checkpoints/pretrained_action_adapter/adapter_config.json

@@ -0,0 +1,33 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "./pretrained/Qwen2_5-1_5B-Instruct",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 256,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 128,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "self_attn.v_proj",
+    "self_attn.o_proj",
+    "self_attn.k_proj",
+    "mlp.down_proj",
+    "self_attn.q_proj",
+    "mlp.up_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

checkpoints/pretrained_action_adapter/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9ceb5d775f50450cbddf740df65f06adf155a5e1b41151e5521f60e7d8cbae02
+size 440447544

checkpoints/step-034500-epoch-08-loss=0.1167.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0fe551dd7afca26cdc389caae3a136e582153b4e0b0d330cd7126a9288d1a00e
+size 11459391954

checkpoints/step-034500-epoch-08_unload_lora.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e2f53755ed37fb002edf1622c44beef6c6e64adb2c90627a3bdb23f397a3836f
+size 10086638182

config.json

@@ -0,0 +1,55 @@
+{
+  "action_dim": 7,
+  "action_model_type": "DiT-B",
+  "data_root_dir": "s3://real_data_raw/open_x_embodiment_origin",
+  "debug": false,
+  "future_action_window_size": 15,
+  "hf_token": "hf_token",
+  "image_aug": true,
+  "is_resume": true,
+  "load_all_data_for_training": true,
+  "past_action_window_size": 0,
+  "pretrained_checkpoint": "/mnt/petrelfs/yangshuai1/rep/cogact_with_history/outputs/head_balation/sys12_meta_query_action_only_sync_pretraining_v2_query_64_mlp_lora--image_aug/checkpoints/step-027000-epoch-07-loss=0.1102.pt",
+  "repeated_diffusion_steps": 4,
+  "resume_epoch": 7,
+  "resume_step": 27000,
+  "run_id": "sys12_meta_query_action_only_sync_pretraining_v2_query_64_mlp_lora--image_aug",
+  "run_id_note": null,
+  "run_root_dir": "outputs/head_balation",
+  "save_interval": 1500,
+  "seed": 42,
+  "stage": "stage1",
+  "trackers": [
+    "jsonl",
+    "wandb"
+  ],
+  "use_ema": false,
+  "use_mm": false,
+  "vla": {
+    "action_tokenizer": "extra_action_tokenizer",
+    "base_vlm": "/mnt/petrelfs/yangshuai1/yangshuai1/share_mllm/Eagle2-2B",
+    "data_mix": "bridge_rt_1",
+    "enable_gradient_checkpointing": true,
+    "enable_mixed_precision_training": true,
+    "epochs": 100,
+    "expected_world_size": 96,
+    "freeze_llm_backbone": false,
+    "freeze_vision_backbone": false,
+    "global_batch_size": 1536,
+    "learning_rate": 5e-05,
+    "lr_scheduler_type": "constant",
+    "max_grad_norm": 1.0,
+    "max_steps": null,
+    "per_device_batch_size": 16,
+    "reduce_in_full_precision": true,
+    "shuffle_buffer_size": 250000,
+    "train_strategy": "fsdp-shard-grad-op",
+    "type": "prism-qwen25-dinosiglip-224px+0_5b",
+    "unfreeze_last_llm_layer": false,
+    "vla_id": "prism-qwen25-dinosiglip-224px+0_5b",
+    "warmup_ratio": 0.0,
+    "weight_decay": 0.0
+  },
+  "wandb_entity": "shuaiyang2003",
+  "wandb_project": "dual_sys"
+}

config.yaml

@@ -0,0 +1,51 @@
+action_dim: 7
+action_model_type: DiT-B
+data_root_dir: s3://real_data_raw/open_x_embodiment_origin
+debug: false
+future_action_window_size: 15
+hf_token: hf_token
+image_aug: true
+is_resume: true
+load_all_data_for_training: true
+past_action_window_size: 0
+pretrained_checkpoint: /mnt/petrelfs/yangshuai1/rep/cogact_with_history/outputs/head_balation/sys12_meta_query_action_only_sync_pretraining_v2_query_64_mlp_lora--image_aug/checkpoints/step-027000-epoch-07-loss=0.1102.pt
+repeated_diffusion_steps: 4
+resume_epoch: 7
+resume_step: 27000
+run_id: sys12_meta_query_action_only_sync_pretraining_v2_query_64_mlp_lora--image_aug
+run_id_note: null
+run_root_dir: outputs/head_balation
+save_interval: 1500
+seed: 42
+stage: stage1
+trackers:
+- jsonl
+- wandb
+use_ema: false
+use_mm: false
+vla:
+  action_tokenizer: extra_action_tokenizer
+  base_vlm: /mnt/petrelfs/yangshuai1/yangshuai1/share_mllm/Eagle2-2B
+  data_mix: bridge_rt_1
+  enable_gradient_checkpointing: true
+  enable_mixed_precision_training: true
+  epochs: 100
+  expected_world_size: 96
+  freeze_llm_backbone: false
+  freeze_vision_backbone: false
+  global_batch_size: 1536
+  learning_rate: 5.0e-05
+  lr_scheduler_type: constant
+  max_grad_norm: 1.0
+  max_steps: null
+  per_device_batch_size: 16
+  reduce_in_full_precision: true
+  shuffle_buffer_size: 250000
+  train_strategy: fsdp-shard-grad-op
+  type: prism-qwen25-dinosiglip-224px+0_5b
+  unfreeze_last_llm_layer: false
+  vla_id: prism-qwen25-dinosiglip-224px+0_5b
+  warmup_ratio: 0.0
+  weight_decay: 0.0
+wandb_entity: shuaiyang2003
+wandb_project: dual_sys

dataset_statistics.json

@@ -0,0 +1,252 @@
+{
+  "bridge_dataset": {
+    "action": {
+      "mean": [
+        0.0002334193413844332,
+        0.0001300490548601374,
+        -0.0001276246621273458,
+        -0.00015565502690151334,
+        -0.0004039333143737167,
+        0.0002355769247515127,
+        0.5764579772949219
+      ],
+      "std": [
+        0.009765916503965855,
+        0.013689138926565647,
+        0.012667354196310043,
+        0.02853417582809925,
+        0.0306379534304142,
+        0.07691461592912674,
+        0.49737000465393066
+      ],
+      "max": [
+        0.41691166162490845,
+        0.25864794850349426,
+        0.21218234300613403,
+        3.122201919555664,
+        1.8618112802505493,
+        6.280478477478027,
+        1.0
+      ],
+      "min": [
+        -0.4007510244846344,
+        -0.13874775171279907,
+        -0.22553899884223938,
+        -3.2010786533355713,
+        -1.8618112802505493,
+        -6.279075622558594,
+        0.0
+      ],
+      "q01": [
+        -0.02872725307941437,
+        -0.04170349963009357,
+        -0.026093858778476715,
+        -0.08092105075716972,
+        -0.09288699507713317,
+        -0.20718276381492615,
+        0.0
+      ],
+      "q99": [
+        0.028309678435325586,
+        0.040855254605412394,
+        0.040161586627364146,
+        0.08192047759890528,
+        0.07792850524187081,
+        0.20382574498653397,
+        1.0
+      ],
+      "mask": [
+        true,
+        true,
+        true,
+        true,
+        true,
+        true,
+        false
+      ]
+    },
+    "proprio": {
+      "mean": [
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0
+      ],
+      "std": [
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0
+      ],
+      "max": [
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0
+      ],
+      "min": [
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0
+      ],
+      "q01": [
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0
+      ],
+      "q99": [
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0
+      ]
+    },
+    "num_transitions": 2135463,
+    "num_trajectories": 60064
+  },
+  "fractal20220817_data": {
+    "action": {
+      "mean": [
+        0.006987507455050945,
+        0.0062658516690135,
+        -0.012625164352357388,
+        0.04333285614848137,
+        -0.005756272468715906,
+        0.0009130411199294031,
+        0.5354204773902893
+      ],
+      "std": [
+        0.06921109557151794,
+        0.05970890820026398,
+        0.0735311210155487,
+        0.15610598027706146,
+        0.1316441297531128,
+        0.1459376960992813,
+        0.49711623787879944
+      ],
+      "max": [
+        2.9984593391418457,
+        22.09052848815918,
+        2.7507524490356445,
+        1.570636510848999,
+        1.5321086645126343,
+        1.5691522359848022,
+        1.0
+      ],
+      "min": [
+        -2.0204520225524902,
+        -5.497899532318115,
+        -2.031663417816162,
+        -1.569917917251587,
+        -1.569892168045044,
+        -1.570419430732727,
+        0.0
+      ],
+      "q01": [
+        -0.22453527510166169,
+        -0.14820013284683228,
+        -0.231589707583189,
+        -0.3517994859814644,
+        -0.4193011274933815,
+        -0.43643461108207704,
+        0.0
+      ],
+      "q99": [
+        0.17824687153100965,
+        0.14938379630446405,
+        0.21842354819178575,
+        0.5892666035890578,
+        0.35272657424211445,
+        0.44796681255102094,
+        1.0
+      ],
+      "mask": [
+        true,
+        true,
+        true,
+        true,
+        true,
+        true,
+        false
+      ]
+    },
+    "proprio": {
+      "mean": [
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0
+      ],
+      "std": [
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0
+      ],
+      "max": [
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0
+      ],
+      "min": [
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0
+      ],
+      "q01": [
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0
+      ],
+      "q99": [
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0
+      ]
+    },
+    "num_transitions": 3786400,
+    "num_trajectories": 87212
+  }
+}

results_step-034500-epoch-08-loss=0.1167_1/log/final_result.log

@@ -0,0 +1,114 @@
+***Pick coke can results***
+--------------------
+horizontal sim variant avg success {'CogACT-Base': 0.8933333333333334}
+vertical sim variant avg success {'CogACT-Base': 0.9155555555555553}
+standing sim variant avg success {'CogACT-Base': 0.9644444444444444}
+avg_orientation_sim_variant_results [0.9244444444444445]
+--------------------
+Orientation horizontal, ckpt CogACT-Base all robot arm visual matching success: [0.8, 0.76, 0.8, 0.92]
+Orientation vertical, ckpt CogACT-Base all robot arm visual matching success: [0.8, 0.84, 0.84, 0.88]
+Orientation standing, ckpt CogACT-Base all robot arm visual matching success: [0.84, 0.76, 0.88, 0.68]
+horizontal visual matching sim success {'CogACT-Base': 0.8200000000000001}
+vertical visual matching sim success {'CogACT-Base': 0.84}
+standing visual matching sim success {'CogACT-Base': 0.79}
+avg_orientation_sim_visual_matching_results [0.8166666666666668]
+********************
+
+
+
+***Move Near results***
+--------------------
+sim variant avg success {'CogACT-Base': 0.7083333333333333}
+--------------------
+Ckpt CogACT-Base all robot arm visual matching success: [0.65, 0.5833333333333334, 0.6333333333333333, 0.7333333333333333]
+sim visual matching success {'CogACT-Base': 0.65}
+********************
+
+
+
+***Drawer results***
+--------------------
+open sim variant avg success {'CogACT-Base': 0.41269841269841256}
+close sim variant avg success {'CogACT-Base': 0.8042328042328041}
+avg_sim_variant_results [0.6084656084656084]
+--------------------
+Drawer task open, ckpt CogACT-Base all robot arm visual matching success: [0.41666666666666663, 0.33333333333333337, 0.4444444444444444, 0.4074074074074074]
+Drawer task close, ckpt CogACT-Base all robot arm visual matching success: [0.6666666666666667, 0.6111111111111112, 0.5555555555555556, 0.6296296296296297]
+open visual matching sim success {'CogACT-Base': 0.39814814814814814}
+close visual matching sim success {'CogACT-Base': 0.6111111111111112}
+avg_sim_visual_matching_results [0.5046296296296297]
+********************
+
+
+
+***Drawer results***
+--------------------
+put_apple_into_top_drawer sim variant avg success {'CogACT-Base': 0.3174603174603175}
+avg_sim_variant_results [0.3174603174603175]
+--------------------
+Drawer task put_apple_into_top_drawer, ckpt CogACT-Base all robot arm visual matching success: [0.5462962962962963, 0.5555555555555555, 0.5185185185185185, 0.5925925925925926]
+put_apple_into_top_drawer visual matching sim success {'CogACT-Base': 0.5462962962962963}
+avg_sim_visual_matching_results [0.5462962962962963]
+********************
+
+
+
+***Bridge Put On Env results***
+********** Results for put_spoon_on_tablecloth **********
+sim visual matching partial success {'CogACT-Base': 0.7083333333333334}
+sim visual matching success {'CogACT-Base': 0.4166666666666667}
+********************
+
+
+
+********** Results for put_carrot_on_plate **********
+sim visual matching partial success {'CogACT-Base': 0.4583333333333333}
+sim visual matching success {'CogACT-Base': 0.4166666666666667}
+********************
+
+
+
+********** Results for stack_green_block_on_yellow_block **********
+sim visual matching partial success {'CogACT-Base': 0.25}
+sim visual matching success {'CogACT-Base': 0.041666666666666664}
+********************
+
+
+
+********** Results for put_eggplant_in_basket **********
+sim visual matching partial success {'CogACT-Base': 0.9166666666666666}
+sim visual matching success {'CogACT-Base': 0.9166666666666666}
+********************
+
+
+
+
+google_var:
+92.4
+92.4
+70.8
+70.8
+60.8
+60.8
+31.7
+31.7
+
+google_matching
+81.7
+81.7
+65.0
+65.0
+50.5
+50.5
+54.6
+54.6
+
+widowx_matching
+41.7
+41.7
+41.7
+41.7
+4.2
+4.2
+91.7
+91.7

results_step-034500-epoch-08-loss=0.1167_1/log/log3.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:097a46ea879d719664fd6d539f95634ae4d20ad054ecdb34c476617e54047c9f
+size 13950946

results_step-034500-epoch-08-loss=0.1167_1/log/log7.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5b181b800986a26cdc8cd9078470b5f538c6b34428792a36988e52fb7add1653
+size 26766431

results_step-034500-epoch-08-loss=0.1167_2/log/final_result.log

@@ -0,0 +1,114 @@
+***Pick coke can results***
+--------------------
+horizontal sim variant avg success {'CogACT-Base': 0.88}
+vertical sim variant avg success {'CogACT-Base': 0.8961111111111111}
+standing sim variant avg success {'CogACT-Base': 0.9688888888888888}
+avg_orientation_sim_variant_results [0.915]
+--------------------
+Orientation horizontal, ckpt CogACT-Base all robot arm visual matching success: [0.88, 0.68, 0.68, 0.92]
+Orientation vertical, ckpt CogACT-Base all robot arm visual matching success: [0.84, 0.8, 0.8, 0.8]
+Orientation standing, ckpt CogACT-Base all robot arm visual matching success: [0.92, 0.8, 0.8, 0.56]
+horizontal visual matching sim success {'CogACT-Base': 0.79}
+vertical visual matching sim success {'CogACT-Base': 0.81}
+standing visual matching sim success {'CogACT-Base': 0.7700000000000001}
+avg_orientation_sim_visual_matching_results [0.79]
+********************
+
+
+
+***Move Near results***
+--------------------
+sim variant avg success {'CogACT-Base': 0.7333333333333334}
+--------------------
+Ckpt CogACT-Base all robot arm visual matching success: [0.75, 0.6666666666666666, 0.6333333333333333, 0.8]
+sim visual matching success {'CogACT-Base': 0.7124999999999999}
+********************
+
+
+
+***Drawer results***
+--------------------
+open sim variant avg success {'CogACT-Base': 0.41798941798941797}
+close sim variant avg success {'CogACT-Base': 0.8201058201058201}
+avg_sim_variant_results [0.6190476190476191]
+--------------------
+Drawer task open, ckpt CogACT-Base all robot arm visual matching success: [0.5, 0.36111111111111105, 0.3333333333333333, 0.5185185185185185]
+Drawer task close, ckpt CogACT-Base all robot arm visual matching success: [0.7499999999999999, 0.5277777777777778, 0.6388888888888888, 0.7037037037037037]
+open visual matching sim success {'CogACT-Base': 0.3981481481481481}
+close visual matching sim success {'CogACT-Base': 0.6388888888888888}
+avg_sim_visual_matching_results [0.5185185185185185]
+********************
+
+
+
+***Drawer results***
+--------------------
+put_apple_into_top_drawer sim variant avg success {'CogACT-Base': 0.3174603174603175}
+avg_sim_variant_results [0.3174603174603175]
+--------------------
+Drawer task put_apple_into_top_drawer, ckpt CogACT-Base all robot arm visual matching success: [0.4722222222222222, 0.49382716049382713, 0.5185185185185185, 0.5185185185185185]
+put_apple_into_top_drawer visual matching sim success {'CogACT-Base': 0.4722222222222222}
+avg_sim_visual_matching_results [0.4722222222222222]
+********************
+
+
+
+***Bridge Put On Env results***
+********** Results for put_spoon_on_tablecloth **********
+sim visual matching partial success {'CogACT-Base': 0.7083333333333334}
+sim visual matching success {'CogACT-Base': 0.375}
+********************
+
+
+
+********** Results for put_carrot_on_plate **********
+sim visual matching partial success {'CogACT-Base': 0.5}
+sim visual matching success {'CogACT-Base': 0.25}
+********************
+
+
+
+********** Results for stack_green_block_on_yellow_block **********
+sim visual matching partial success {'CogACT-Base': 0.25}
+sim visual matching success {'CogACT-Base': 0.041666666666666664}
+********************
+
+
+
+********** Results for put_eggplant_in_basket **********
+sim visual matching partial success {'CogACT-Base': 0.9583333333333334}
+sim visual matching success {'CogACT-Base': 0.9583333333333334}
+********************
+
+
+
+
+google_var:
+91.5
+91.5
+73.3
+73.3
+61.9
+61.9
+31.7
+31.7
+
+google_matching
+79.0
+79.0
+71.2
+71.2
+51.9
+51.9
+47.2
+47.2
+
+widowx_matching
+37.5
+37.5
+25.0
+25.0
+4.2
+4.2
+95.8
+95.8

results_step-034500-epoch-08-loss=0.1167_2/log/log3.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3f6dae1e4322d9a1f58d3777a97bed777636d56bb02e40da1587bb906f2f64da
+size 13613304

results_step-034500-epoch-08-loss=0.1167_2/log/log7.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c4b02c83c3e90d382166f97d9f737becd0cf23467438387f3cd77f81930ed8a1
+size 26763867

results_step-034500-epoch-08-loss=0.1167_3/log/final_result.log

@@ -0,0 +1,114 @@
+***Pick coke can results***
+--------------------
+horizontal sim variant avg success {'CogACT-Base': 0.8977777777777778}
+vertical sim variant avg success {'CogACT-Base': 0.9066666666666667}
+standing sim variant avg success {'CogACT-Base': 0.9822222222222222}
+avg_orientation_sim_variant_results [0.9288888888888889]
+--------------------
+Orientation horizontal, ckpt CogACT-Base all robot arm visual matching success: [0.88, 0.92, 0.84, 0.92]
+Orientation vertical, ckpt CogACT-Base all robot arm visual matching success: [0.8, 0.76, 0.8, 0.8]
+Orientation standing, ckpt CogACT-Base all robot arm visual matching success: [0.76, 0.6, 0.52, 0.76]
+horizontal visual matching sim success {'CogACT-Base': 0.89}
+vertical visual matching sim success {'CogACT-Base': 0.79}
+standing visual matching sim success {'CogACT-Base': 0.6599999999999999}
+avg_orientation_sim_visual_matching_results [0.7799999999999999]
+********************
+
+
+
+***Move Near results***
+--------------------
+sim variant avg success {'CogACT-Base': 0.7166666666666667}
+--------------------
+Ckpt CogACT-Base all robot arm visual matching success: [0.7166666666666667, 0.6833333333333333, 0.6833333333333333, 0.6666666666666666]
+sim visual matching success {'CogACT-Base': 0.6874999999999999}
+********************
+
+
+
+***Drawer results***
+--------------------
+open sim variant avg success {'CogACT-Base': 0.43386243386243384}
+close sim variant avg success {'CogACT-Base': 0.8148148148148148}
+avg_sim_variant_results [0.6243386243386243]
+--------------------
+Drawer task open, ckpt CogACT-Base all robot arm visual matching success: [0.4722222222222222, 0.41666666666666663, 0.5, 0.4444444444444444]
+Drawer task close, ckpt CogACT-Base all robot arm visual matching success: [0.6666666666666667, 0.6111111111111112, 0.611111111111111, 0.6666666666666666]
+open visual matching sim success {'CogACT-Base': 0.46296296296296297}
+close visual matching sim success {'CogACT-Base': 0.6296296296296297}
+avg_sim_visual_matching_results [0.5462962962962963]
+********************
+
+
+
+***Drawer results***
+--------------------
+put_apple_into_top_drawer sim variant avg success {'CogACT-Base': 0.3597883597883597}
+avg_sim_variant_results [0.3597883597883597]
+--------------------
+Drawer task put_apple_into_top_drawer, ckpt CogACT-Base all robot arm visual matching success: [0.49074074074074076, 0.49382716049382713, 0.4814814814814815, 0.4074074074074074]
+put_apple_into_top_drawer visual matching sim success {'CogACT-Base': 0.49074074074074076}
+avg_sim_visual_matching_results [0.49074074074074076]
+********************
+
+
+
+***Bridge Put On Env results***
+********** Results for put_spoon_on_tablecloth **********
+sim visual matching partial success {'CogACT-Base': 0.7083333333333334}
+sim visual matching success {'CogACT-Base': 0.5}
+********************
+
+
+
+********** Results for put_carrot_on_plate **********
+sim visual matching partial success {'CogACT-Base': 0.625}
+sim visual matching success {'CogACT-Base': 0.5416666666666666}
+********************
+
+
+
+********** Results for stack_green_block_on_yellow_block **********
+sim visual matching partial success {'CogACT-Base': 0.4583333333333333}
+sim visual matching success {'CogACT-Base': 0.20833333333333334}
+********************
+
+
+
+********** Results for put_eggplant_in_basket **********
+sim visual matching partial success {'CogACT-Base': 0.9583333333333334}
+sim visual matching success {'CogACT-Base': 0.9583333333333334}
+********************
+
+
+
+
+google_var:
+92.9
+92.9
+71.7
+71.7
+62.4
+62.4
+36.0
+36.0
+
+google_matching
+78.0
+78.0
+68.7
+68.7
+54.6
+54.6
+49.1
+49.1
+
+widowx_matching
+50.0
+50.0
+54.2
+54.2
+20.8
+20.8
+95.8
+95.8

results_step-034500-epoch-08-loss=0.1167_3/log/log3.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7dd33c4ea1e4a616f334beadef0a3e837501f663bc73725c20b7979fa7037cb9
+size 13947517

results_step-034500-epoch-08-loss=0.1167_3/log/log7.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8d7ece15dd75e3c0570d4406e9e628baa6283d566c137e0b2b236559450832ba
+size 26771347

results_step-034500-epoch-08-loss=0.1167_instruct_1/log/final_results_instruct.log

@@ -0,0 +1,85 @@
+Category,Task,Success_Rate
+Free,FreeCloseBottomDrawerCustomInScene-v0,0.3529
+Free,FreeCloseBottomDrawerCustomInScene-v1,0.0000
+Free,FreeCloseMiddleDrawerCustomInScene-v0,0.2500
+Free,FreeCloseMiddleDrawerCustomInScene-v1,0.0833
+Free,FreeCloseTopDrawerCustomInScene-v0,0.8462
+Free,FreeCloseTopDrawerCustomInScene-v1,0.4615
+Free,FreeGraspSingle7upCanInScene-v0,0.5000
+Free,FreeGraspSingle7upCanInScene-v1,0.1212
+Free,FreeGraspSingle7upCanInScene-v2,0.0000
+Free,FreeGraspSingleBananaInScene-v0,0.5333
+Free,FreeGraspSingleBananaInScene-v1,0.2727
+Free,FreeGraspSingleBananaInScene-v2,0.0000
+Free,FreeGraspSingleLemonInScene-v0,0.5161
+Free,FreeGraspSingleLemonInScene-v1,0.0952
+Free,FreeGraspSingleLemonInScene-v2,0.4615
+Free,FreeGraspSingleOpened7upCanInScene-v0,0.0882
+Free,FreeGraspSingleOpened7upCanInScene-v1,0.0278
+Free,FreeGraspSingleOpenedPepsiCanInScene-v0,0.1875
+Free,FreeGraspSingleOpenedPepsiCanInScene-v1,0.4103
+Free,FreeGraspSingleOrangeInScene-v0,0.0000
+Free,FreeGraspSingleOrangeInScene-v1,0.2273
+Free,FreeGraspSinglePearInScene-v0,0.5862
+Free,FreeGraspSinglePearInScene-v1,0.0000
+Free,FreeGraspSinglePearInScene-v2,0.0000
+Free,FreeGraspSinglePlumInScene-v0,0.1000
+Free,FreeGraspSinglePlumInScene-v1,0.3077
+Free,FreeGraspSinglePumpkinInScene-v0,0.0000
+Free,FreeGraspSinglePumpkinInScene-v1,0.0000
+Free,FreeGraspSingleSpriteCanInScene-v0,0.0000
+Free,FreeGraspSingleSpriteCanInScene-v1,0.0000
+Free,FreeGraspSingleSpriteCanInScene-v2,0.0000
+Free,FreeOpenBottomDrawerCustomInScene-v0,0.0000
+Free,FreeOpenBottomDrawerCustomInScene-v1,0.0000
+Free,FreeOpenMiddleDrawerCustomInScene-v0,0.4375
+Free,FreeOpenMiddleDrawerCustomInScene-v1,0.2143
+Free,FreeOpenTopDrawerCustomInScene-v0,0.2667
+Free,FreeOpenTopDrawerCustomInScene-v1,0.4000
+Free,FreePlaceBottleNearOrangeEnv-v0,0.3889
+Free,FreePlaceIntoTopDrawerEnv-v0,0.6111
+Free,FreePlaceIntoTopDrawerEnv-v1,0.5556
+Free,FreePlaceIntoTopDrawerEnv-v2,0.6667
+Free,FreePlaceLNearAEnv-v0,0.3333
+Free,FreePlaceLNearVEnv-v0,0.5000
+Free,FreePlaceLemonNearPearEnv-v0,0.4000
+Free,FreePlaceLemonNearPearEnv-v1,0.0000
+Free,FreePlaceLemonNearPearEnv-v2,0.0000
+Free,FreePlaceMugNearPlaystationEnv-v0,0.1176
+Free,FreePlaceMugNearPlaystationEnv-v0,0.1579
+Free,FreePlaceMugNearPlaystationEnv-v1,0.0667
+Free,FreePlaceMugNearPlaystationEnv-v1,0.1053
+Alt,AltCloseDrawerInLongStep1HorizonInSceneEnv-v0,0.2353
+Alt,AltCloseDrawerInLongStep1HorizonInSceneEnv-v0,0.2500
+Alt,AltCloseDrawerInLongStep2HorizonInSceneEnv-v0,0.1875
+Alt,AltCloseDrawerInLongStep2HorizonInSceneEnv-v0,0.1875
+Alt,AltCloseDrawerInLongStep2HorizonInSceneEnv-v0,0.2353
+Alt,AltCloseMiddleDrawerInLongStep2HorizonInSceneEnv-v0,0.0000
+Alt,AltCloseMiddleDrawerInLongStep2HorizonInSceneEnv-v0,0.0909
+Alt,AltGraspEggplantDistractorInSceneEnv-v0,0.0000
+Alt,AltGraspEggplantDistractorInSceneEnv-v0,0.0556
+Alt,AltGraspMugDistractorInSceneEnv-v0,0.0000
+Alt,AltGraspMugDistractorInSceneEnv-v0,0.0000
+Alt,AltGraspMugDistractorInSceneEnv-v1,0.1500
+Alt,AltGraspMugDistractorInSceneEnv-v1,0.1000
+Alt,AltGraspOrange2DistractorInSceneEnv-v0,0.0000
+Alt,AltGraspOrange2DistractorInSceneEnv-v0,0.0000
+Alt,AltGraspOrangeDistractorInSceneEnv-v0,0.0000
+Alt,AltGraspOrangeDistractorInSceneEnv-v0,0.0000
+Alt,AltGraspSpongeDistractorInSceneEnv-v0,0.0588
+Alt,AltGraspSpongeDistractorInSceneEnv-v0,0.0000
+Alt,AltOpenBottomDrawerCustomInSceneEnv-v0,0.2667
+Alt,AltOpenBottomDrawerCustomInSceneEnv2-v0,0.0909
+Alt,AltOpenMiddleDrawerCustomInSceneEnv-v0,0.5000
+Alt,AltOpenMiddleDrawerCustomInSceneEnv2-v0,0.3125
+Alt,AltOpenTopDrawerCustomInSceneEnv-v0,0.0000
+Alt,AltOpenTopDrawerCustomInSceneEnv2-v0,0.2667
+Alt,AltPlaceAppleNearOrangeCanEnv-v0,0.0000
+Alt,AltPlaceBottleNearOrangeEnv-v0,0.0000
+Alt,AltPlaceBottleNearSpongeEnv-v0,0.7333
+Alt,AltPutOrangeOnPlateInScene-v0,0.0000
+Alt,AltPutSponeOnPlateInScene-v0,0.0400
+
+Category,Average_Success_Rate
+Free,0.2330
+Alt,0.1254

results_step-034500-epoch-08-loss=0.1167_instruct_2/log/final_results_instruct.log

@@ -0,0 +1,85 @@
+Category,Task,Success_Rate
+Free,FreeCloseBottomDrawerCustomInScene-v0,0.4444
+Free,FreeCloseBottomDrawerCustomInScene-v1,0.0000
+Free,FreeCloseMiddleDrawerCustomInScene-v0,0.2222
+Free,FreeCloseMiddleDrawerCustomInScene-v1,0.0000
+Free,FreeCloseTopDrawerCustomInScene-v0,1.0000
+Free,FreeCloseTopDrawerCustomInScene-v1,0.7778
+Free,FreeGraspSingle7upCanInScene-v0,0.4000
+Free,FreeGraspSingle7upCanInScene-v1,0.0400
+Free,FreeGraspSingle7upCanInScene-v2,0.0000
+Free,FreeGraspSingleBananaInScene-v0,0.5000
+Free,FreeGraspSingleBananaInScene-v1,0.1875
+Free,FreeGraspSingleBananaInScene-v2,0.0000
+Free,FreeGraspSingleLemonInScene-v0,0.4375
+Free,FreeGraspSingleLemonInScene-v1,0.0625
+Free,FreeGraspSingleLemonInScene-v2,0.1875
+Free,FreeGraspSingleOpened7upCanInScene-v0,0.0000
+Free,FreeGraspSingleOpened7upCanInScene-v1,0.0400
+Free,FreeGraspSingleOpenedPepsiCanInScene-v0,0.1200
+Free,FreeGraspSingleOpenedPepsiCanInScene-v1,0.2800
+Free,FreeGraspSingleOrangeInScene-v0,0.0000
+Free,FreeGraspSingleOrangeInScene-v1,0.0625
+Free,FreeGraspSinglePearInScene-v0,0.8750
+Free,FreeGraspSinglePearInScene-v1,0.0000
+Free,FreeGraspSinglePearInScene-v2,0.0000
+Free,FreeGraspSinglePlumInScene-v0,0.0000
+Free,FreeGraspSinglePlumInScene-v1,0.3125
+Free,FreeGraspSinglePumpkinInScene-v0,0.0000
+Free,FreeGraspSinglePumpkinInScene-v1,0.0000
+Free,FreeGraspSingleSpriteCanInScene-v0,0.0400
+Free,FreeGraspSingleSpriteCanInScene-v1,0.0000
+Free,FreeGraspSingleSpriteCanInScene-v2,0.0000
+Free,FreeOpenBottomDrawerCustomInScene-v0,0.0000
+Free,FreeOpenBottomDrawerCustomInScene-v1,0.0000
+Free,FreeOpenMiddleDrawerCustomInScene-v0,0.3333
+Free,FreeOpenMiddleDrawerCustomInScene-v1,0.1111
+Free,FreeOpenTopDrawerCustomInScene-v0,0.2222
+Free,FreeOpenTopDrawerCustomInScene-v1,0.2222
+Free,FreePlaceBottleNearOrangeEnv-v0,0.4167
+Free,FreePlaceIntoTopDrawerEnv-v0,0.8889
+Free,FreePlaceIntoTopDrawerEnv-v1,0.4444
+Free,FreePlaceIntoTopDrawerEnv-v2,0.4444
+Free,FreePlaceLNearAEnv-v0,0.3333
+Free,FreePlaceLNearVEnv-v0,0.3333
+Free,FreePlaceLemonNearPearEnv-v0,0.6667
+Free,FreePlaceLemonNearPearEnv-v1,0.0000
+Free,FreePlaceLemonNearPearEnv-v2,0.0000
+Free,FreePlaceMugNearPlaystationEnv-v0,0.0000
+Free,FreePlaceMugNearPlaystationEnv-v0,0.0000
+Free,FreePlaceMugNearPlaystationEnv-v1,0.0833
+Free,FreePlaceMugNearPlaystationEnv-v1,0.0000
+Alt,AltCloseDrawerInLongStep1HorizonInSceneEnv-v0,0.2222
+Alt,AltCloseDrawerInLongStep1HorizonInSceneEnv-v0,0.2222
+Alt,AltCloseDrawerInLongStep2HorizonInSceneEnv-v0,0.1111
+Alt,AltCloseDrawerInLongStep2HorizonInSceneEnv-v0,0.3333
+Alt,AltCloseDrawerInLongStep2HorizonInSceneEnv-v0,0.2222
+Alt,AltCloseMiddleDrawerInLongStep2HorizonInSceneEnv-v0,0.0000
+Alt,AltCloseMiddleDrawerInLongStep2HorizonInSceneEnv-v0,0.0000
+Alt,AltGraspEggplantDistractorInSceneEnv-v0,0.0000
+Alt,AltGraspEggplantDistractorInSceneEnv-v0,0.0000
+Alt,AltGraspMugDistractorInSceneEnv-v0,0.0625
+Alt,AltGraspMugDistractorInSceneEnv-v0,0.0000
+Alt,AltGraspMugDistractorInSceneEnv-v1,0.0625
+Alt,AltGraspMugDistractorInSceneEnv-v1,0.0000
+Alt,AltGraspOrange2DistractorInSceneEnv-v0,0.0000
+Alt,AltGraspOrange2DistractorInSceneEnv-v0,0.0000
+Alt,AltGraspOrangeDistractorInSceneEnv-v0,0.0000
+Alt,AltGraspOrangeDistractorInSceneEnv-v0,0.0000
+Alt,AltGraspSpongeDistractorInSceneEnv-v0,0.0000
+Alt,AltGraspSpongeDistractorInSceneEnv-v0,0.0000
+Alt,AltOpenBottomDrawerCustomInSceneEnv-v0,0.3333
+Alt,AltOpenBottomDrawerCustomInSceneEnv2-v0,0.2222
+Alt,AltOpenMiddleDrawerCustomInSceneEnv-v0,0.4444
+Alt,AltOpenMiddleDrawerCustomInSceneEnv2-v0,0.4444
+Alt,AltOpenTopDrawerCustomInSceneEnv-v0,0.1111
+Alt,AltOpenTopDrawerCustomInSceneEnv2-v0,0.4444
+Alt,AltPlaceAppleNearOrangeCanEnv-v0,0.0000
+Alt,AltPlaceBottleNearOrangeEnv-v0,0.1667
+Alt,AltPlaceBottleNearSpongeEnv-v0,0.5833
+Alt,AltPutOrangeOnPlateInScene-v0,0.0417
+Alt,AltPutSponeOnPlateInScene-v0,0.0000
+
+Category,Average_Success_Rate
+Free,0.2098
+Alt,0.1343