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Unverified Commit 017b6bb3 authored by Rhett Ying's avatar Rhett Ying Committed by GitHub
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[doc] update YAML spec (#6812)

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notebooks/stochastic_training/ondisk_dataset_heterograph.ipynb
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...@@ -524,105 +524,101 @@ ...@@ -524,105 +524,101 @@
" - name: node_classification\n", " - name: node_classification\n",
" num_classes: 10\n", " num_classes: 10\n",
" train_set:\n", " train_set:\n",
" - data:\n", " - type: user\n",
" - type: user\n", " data:\n",
" name: seed_nodes\n", " - name: seed_nodes\n",
" format: numpy\n", " format: numpy\n",
" path: {os.path.basename(nc_train_user_ids_path)}\n", " path: {os.path.basename(nc_train_user_ids_path)}\n",
" - type: user\n", " - name: labels\n",
" name: labels\n",
" format: torch\n", " format: torch\n",
" path: {os.path.basename(nc_train_user_labels_path)}\n", " path: {os.path.basename(nc_train_user_labels_path)}\n",
" - type: item\n", " - type: item\n",
" name: seed_nodes\n", " data:\n",
" - name: seed_nodes\n",
" format: numpy\n", " format: numpy\n",
" path: {os.path.basename(nc_train_item_ids_path)}\n", " path: {os.path.basename(nc_train_item_ids_path)}\n",
" - type: item\n", " - name: labels\n",
" name: labels\n",
" format: torch\n", " format: torch\n",
" path: {os.path.basename(nc_train_item_labels_path)}\n", " path: {os.path.basename(nc_train_item_labels_path)}\n",
" validation_set:\n", " validation_set:\n",
" - data:\n", " - type: user\n",
" - type: user\n", " data:\n",
" name: seed_nodes\n", " - name: seed_nodes\n",
" format: numpy\n", " format: numpy\n",
" path: {os.path.basename(nc_val_user_ids_path)}\n", " path: {os.path.basename(nc_val_user_ids_path)}\n",
" - type: user\n", " - name: labels\n",
" name: labels\n",
" format: torch\n", " format: torch\n",
" path: {os.path.basename(nc_val_user_labels_path)}\n", " path: {os.path.basename(nc_val_user_labels_path)}\n",
" - type: item\n", " - type: item\n",
" name: seed_nodes\n", " data:\n",
" - name: seed_nodes\n",
" format: numpy\n", " format: numpy\n",
" path: {os.path.basename(nc_val_item_ids_path)}\n", " path: {os.path.basename(nc_val_item_ids_path)}\n",
" - type: item\n", " - name: labels\n",
" name: labels\n",
" format: torch\n", " format: torch\n",
" path: {os.path.basename(nc_val_item_labels_path)}\n", " path: {os.path.basename(nc_val_item_labels_path)}\n",
" test_set:\n", " test_set:\n",
" - data:\n", " - type: user\n",
" - type: user\n", " data:\n",
" name: seed_nodes\n", " - name: seed_nodes\n",
" format: numpy\n", " format: numpy\n",
" path: {os.path.basename(nc_test_user_ids_path)}\n", " path: {os.path.basename(nc_test_user_ids_path)}\n",
" - type: user\n", " - name: labels\n",
" name: labels\n",
" format: torch\n", " format: torch\n",
" path: {os.path.basename(nc_test_user_labels_path)}\n", " path: {os.path.basename(nc_test_user_labels_path)}\n",
" - type: item\n", " - type: item\n",
" name: seed_nodes\n", " data:\n",
" - name: seed_nodes\n",
" format: numpy\n", " format: numpy\n",
" path: {os.path.basename(nc_test_item_ids_path)}\n", " path: {os.path.basename(nc_test_item_ids_path)}\n",
" - type: item\n", " - name: labels\n",
" name: labels\n",
" format: torch\n", " format: torch\n",
" path: {os.path.basename(nc_test_item_labels_path)}\n", " path: {os.path.basename(nc_test_item_labels_path)}\n",
" - name: link_prediction\n", " - name: link_prediction\n",
" num_classes: 10\n", " num_classes: 10\n",
" train_set:\n", " train_set:\n",
" - data:\n", " - type: \"user:like:item\"\n",
" - type: \"user:like:item\"\n", " data:\n",
" name: node_pairs\n", " - name: node_pairs\n",
" format: numpy\n", " format: numpy\n",
" path: {os.path.basename(lp_train_like_node_pairs_path)}\n", " path: {os.path.basename(lp_train_like_node_pairs_path)}\n",
" - type: \"user:follow:user\"\n", " - type: \"user:follow:user\"\n",
" name: node_pairs\n", " data:\n",
" - name: node_pairs\n",
" format: numpy\n", " format: numpy\n",
" path: {os.path.basename(lp_train_follow_node_pairs_path)}\n", " path: {os.path.basename(lp_train_follow_node_pairs_path)}\n",
" validation_set:\n", " validation_set:\n",
" - data:\n", " - type: \"user:like:item\"\n",
" - type: \"user:like:item\"\n", " data:\n",
" name: node_pairs\n", " - name: node_pairs\n",
" format: numpy\n", " format: numpy\n",
" path: {os.path.basename(lp_val_like_node_pairs_path)}\n", " path: {os.path.basename(lp_val_like_node_pairs_path)}\n",
" - type: \"user:like:item\"\n", " - name: negative_dsts\n",
" name: negative_dsts\n",
" format: torch\n", " format: torch\n",
" path: {os.path.basename(lp_val_like_neg_dsts_path)}\n", " path: {os.path.basename(lp_val_like_neg_dsts_path)}\n",
" - type: \"user:follow:user\"\n", " - type: \"user:follow:user\"\n",
" name: node_pairs\n", " data:\n",
" - name: node_pairs\n",
" format: numpy\n", " format: numpy\n",
" path: {os.path.basename(lp_val_follow_node_pairs_path)}\n", " path: {os.path.basename(lp_val_follow_node_pairs_path)}\n",
" - type: \"user:follow:user\"\n", " - name: negative_dsts\n",
" name: negative_dsts\n",
" format: torch\n", " format: torch\n",
" path: {os.path.basename(lp_val_follow_neg_dsts_path)}\n", " path: {os.path.basename(lp_val_follow_neg_dsts_path)}\n",
" test_set:\n", " test_set:\n",
" - data:\n", " - type: \"user:like:item\"\n",
" - type: \"user:like:item\"\n", " data:\n",
" name: node_pairs\n", " - name: node_pairs\n",
" format: numpy\n", " format: numpy\n",
" path: {os.path.basename(lp_test_like_node_pairs_path)}\n", " path: {os.path.basename(lp_test_like_node_pairs_path)}\n",
" - type: \"user:like:item\"\n", " - name: negative_dsts\n",
" name: negative_dsts\n",
" format: torch\n", " format: torch\n",
" path: {os.path.basename(lp_test_like_neg_dsts_path)}\n", " path: {os.path.basename(lp_test_like_neg_dsts_path)}\n",
" - type: \"user:follow:user\"\n", " - type: \"user:follow:user\"\n",
" name: node_pairs\n", " data:\n",
" - name: node_pairs\n",
" format: numpy\n", " format: numpy\n",
" path: {os.path.basename(lp_test_follow_node_pairs_path)}\n", " path: {os.path.basename(lp_test_follow_node_pairs_path)}\n",
" - type: \"user:follow:user\"\n", " - name: negative_dsts\n",
" name: negative_dsts\n",
" format: torch\n", " format: torch\n",
" path: {os.path.basename(lp_test_follow_neg_dsts_path)}\n", " path: {os.path.basename(lp_test_follow_neg_dsts_path)}\n",
"\"\"\"\n", "\"\"\"\n",
......
python/dgl/graphbolt/impl/ondisk_dataset.py
View file @ 017b6bb3
...@@ -319,34 +319,31 @@ class OnDiskDataset(Dataset): ...@@ -319,34 +319,31 @@ class OnDiskDataset(Dataset):
- name: "edge_classification" - name: "edge_classification"
num_classes: 10 num_classes: 10
train_set: train_set:
- data: # multiple data sources could be specified. - type: paper # could be omitted for homogeneous graph.
- type: paper data: # multiple data sources could be specified.
name: node_pairs - name: node_pairs
format: numpy # Can be numpy or torch. format: numpy # Can be numpy or torch.
in_memory: true # If not specified, default to true. in_memory: true # If not specified, default to true.
path: set/paper-train-node_pairs.npy path: set/paper-train-node_pairs.npy
- type: paper - name: labels
name: labels
format: numpy format: numpy
path: set/paper-train-labels.npy path: set/paper-train-labels.npy
validation_set: validation_set:
- data: - type: paper
- type: paper data:
name: node_pairs - name: node_pairs
format: numpy format: numpy
path: set/paper-validation-node_pairs.npy path: set/paper-validation-node_pairs.npy
- type: paper - name: labels
name: labels
format: numpy format: numpy
path: set/paper-validation-labels.npy path: set/paper-validation-labels.npy
test_set: test_set:
- data: - type: paper
- type: paper data:
name: node_pairs - name: node_pairs
format: numpy format: numpy
path: set/paper-test-node_pairs.npy path: set/paper-test-node_pairs.npy
- type: paper - name: labels
name: labels
format: numpy format: numpy
path: set/paper-test-labels.npy path: set/paper-test-labels.npy
......
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