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Merge branch 'develop' into add_original_names
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‎samples/mmpose/pose_hrformer_base/graph_net.json‎

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{"framework": "torch", "num_devices_required": 1, "num_nodes_required": 1, "dynamic": false, "source": "mmpose", "heuristic_tag": "computer_vision", "dimension_generalization_passes": []}
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{
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"framework": "torch",
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"num_devices_required": 1,
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"num_nodes_required": 1,
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"dynamic": false,
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"source": "mmpose",
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"heuristic_tag": "computer_vision",
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"dimension_generalization_passes": []
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}

‎samples/mmpose/pose_hrformer_base/input_tensor_constraints.py‎

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from sympy import Symbol, Expr, Rel, Eq
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dynamic_dim_constraint_symbols = []
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dynamic_dim_constraint_symbol2example_value = {}

‎samples/mmpose/pose_hrformer_small/graph_net.json‎

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{"framework": "torch", "num_devices_required": 1, "num_nodes_required": 1, "dynamic": false, "source": "mmpose", "heuristic_tag": "computer_vision", "dimension_generalization_passes": []}
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{
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"framework": "torch",
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"num_devices_required": 1,
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"num_nodes_required": 1,
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"dynamic": false,
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"source": "mmpose",
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"heuristic_tag": "computer_vision",
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"dimension_generalization_passes": []
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}

‎samples/mmpose/pose_hrformer_small/input_tensor_constraints.py‎

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from sympy import Symbol, Expr, Rel, Eq
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dynamic_dim_constraint_symbols = []
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dynamic_dim_constraint_symbol2example_value = {}

‎samples/mmseg/ANN_R101/graph_net.json‎

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{"framework": "torch", "num_devices_required": 1, "num_nodes_required": 1, "dynamic": false, "source": "mmseg", "heuristic_tag": "computer_vision", "dimension_generalization_passes": ["naive_call_method_view_pass", "naive_call_method_reshape_pass", "naive_call_method_expand_pass", "non_batch_call_method_expand_pass", "non_batch_call_function_arange_pass", "non_batch_call_function_getitem_slice_pass", "non_batch_call_function_full_pass", "non_batch_call_function_full_plus_one_pass", "non_batch_call_function_zeros_pass", "non_batch_call_function_arange_plus_one_pass"]}
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{
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"framework": "torch",
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"num_devices_required": 1,
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"num_nodes_required": 1,
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"dynamic": false,
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"source": "mmseg",
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"heuristic_tag": "computer_vision",
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"dimension_generalization_passes": [
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"naive_call_method_view_pass",
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"naive_call_method_reshape_pass",
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"naive_call_method_expand_pass",
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"non_batch_call_method_expand_pass",
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"non_batch_call_function_arange_pass",
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"non_batch_call_function_getitem_slice_pass",
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"non_batch_call_function_full_pass",
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"non_batch_call_function_full_plus_one_pass",
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"non_batch_call_function_zeros_pass",
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"non_batch_call_function_arange_plus_one_pass"
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],
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"symbolic_dimension_reifier": "naive_cv_sym_dim_reifier"
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}

‎samples/mmseg/ANN_R50/graph_net.json‎

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{"framework": "torch", "num_devices_required": 1, "num_nodes_required": 1, "dynamic": false, "source": "mmseg", "heuristic_tag": "computer_vision", "dimension_generalization_passes": ["naive_call_method_view_pass", "naive_call_method_reshape_pass", "naive_call_method_expand_pass", "non_batch_call_method_expand_pass", "non_batch_call_function_arange_pass", "non_batch_call_function_getitem_slice_pass", "non_batch_call_function_full_pass", "non_batch_call_function_full_plus_one_pass", "non_batch_call_function_zeros_pass", "non_batch_call_function_arange_plus_one_pass"]}
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{
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"framework": "torch",
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"num_devices_required": 1,
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"num_nodes_required": 1,
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"dynamic": false,
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"source": "mmseg",
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"heuristic_tag": "computer_vision",
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"dimension_generalization_passes": [
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"naive_call_method_view_pass",
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"naive_call_method_reshape_pass",
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"naive_call_method_expand_pass",
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"non_batch_call_method_expand_pass",
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"non_batch_call_function_arange_pass",
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"non_batch_call_function_getitem_slice_pass",
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"non_batch_call_function_full_pass",
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"non_batch_call_function_full_plus_one_pass",
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"non_batch_call_function_zeros_pass",
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"non_batch_call_function_arange_plus_one_pass"
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],
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"symbolic_dimension_reifier": "naive_cv_sym_dim_reifier"
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}

‎samples/mmseg/APCNet_R101/graph_net.json‎

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{"framework": "torch", "num_devices_required": 1, "num_nodes_required": 1, "dynamic": false, "source": "mmseg", "heuristic_tag": "computer_vision", "dimension_generalization_passes": ["naive_call_method_view_pass", "naive_call_method_reshape_pass", "naive_call_method_expand_pass", "non_batch_call_method_expand_pass", "non_batch_call_function_arange_pass", "non_batch_call_function_getitem_slice_pass", "non_batch_call_function_full_pass", "non_batch_call_function_full_plus_one_pass", "non_batch_call_function_zeros_pass", "non_batch_call_function_arange_plus_one_pass"]}
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{
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"framework": "torch",
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"num_devices_required": 1,
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"num_nodes_required": 1,
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"dynamic": false,
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"source": "mmseg",
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"heuristic_tag": "computer_vision",
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"dimension_generalization_passes": [
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"naive_call_method_view_pass",
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"naive_call_method_reshape_pass",
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"naive_call_method_expand_pass",
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"non_batch_call_method_expand_pass",
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"non_batch_call_function_arange_pass",
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"non_batch_call_function_getitem_slice_pass",
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"non_batch_call_function_full_pass",
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"non_batch_call_function_full_plus_one_pass",
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"non_batch_call_function_zeros_pass",
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"non_batch_call_function_arange_plus_one_pass"
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],
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"symbolic_dimension_reifier": "naive_cv_sym_dim_reifier"
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}

‎samples/mmseg/APCNet_R50/graph_net.json‎

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{"framework": "torch", "num_devices_required": 1, "num_nodes_required": 1, "dynamic": false, "source": "mmseg", "heuristic_tag": "computer_vision", "dimension_generalization_passes": ["naive_call_method_view_pass", "naive_call_method_reshape_pass", "naive_call_method_expand_pass", "non_batch_call_method_expand_pass", "non_batch_call_function_arange_pass", "non_batch_call_function_getitem_slice_pass", "non_batch_call_function_full_pass", "non_batch_call_function_full_plus_one_pass", "non_batch_call_function_zeros_pass", "non_batch_call_function_arange_plus_one_pass"]}
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{
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"framework": "torch",
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"num_devices_required": 1,
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"num_nodes_required": 1,
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"dynamic": false,
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"source": "mmseg",
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"heuristic_tag": "computer_vision",
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"dimension_generalization_passes": [
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"naive_call_method_view_pass",
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"naive_call_method_reshape_pass",
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"naive_call_method_expand_pass",
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"non_batch_call_method_expand_pass",
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"non_batch_call_function_arange_pass",
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"non_batch_call_function_getitem_slice_pass",
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"non_batch_call_function_full_pass",
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"non_batch_call_function_full_plus_one_pass",
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"non_batch_call_function_zeros_pass",
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"non_batch_call_function_arange_plus_one_pass"
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],
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"symbolic_dimension_reifier": "naive_cv_sym_dim_reifier"
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}

‎samples/mmseg/EncNet_R101/graph_net.json‎

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{"framework": "torch", "num_devices_required": 1, "num_nodes_required": 1, "dynamic": false, "source": "mmseg", "heuristic_tag": "computer_vision", "dimension_generalization_passes": []}
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{
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"framework": "torch",
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"num_devices_required": 1,
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"num_nodes_required": 1,
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"dynamic": false,
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"source": "mmseg",
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"heuristic_tag": "computer_vision",
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"dimension_generalization_passes": []
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}

‎samples/mmseg/EncNet_R101/input_tensor_constraints.py‎

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from sympy import Symbol, Expr, Rel, Eq
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dynamic_dim_constraint_symbols = []
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dynamic_dim_constraint_symbol2example_value = {}

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