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liaoxin2liaoxin2
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add some code for chip heat
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8 files changed

+300
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‎docs/zh/api/arch.md‎

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@@ -24,7 +24,6 @@
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- USCNN
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- NowcastNet
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- HEDeepONets
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- DGMR
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- ChipDeepONets
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- AutoEncoder
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show_root_heading: true

‎docs/zh/api/data/dataset.md‎

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members:
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- IterableNamedArrayDataset
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- NamedArrayDataset
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- DeepONetArrayDataset
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- ChipHeatDataset
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- CSVDataset
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- IterableCSVDataset
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- ERA5Dataset
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- MeshCylinderDataset
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- RadarDataset
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- build_dataset
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- DGMRDataset
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show_root_heading: true

‎docs/zh/examples/chip_heat.md‎

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‎examples/chip_heat_simulation/chip_heat_simulation.py‎ renamed to ‎examples/chip_heat/chip_heat.py‎

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@@ -198,7 +198,7 @@ def train(cfg: DictConfig):
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top_sup_constraint = ppsci.constraint.SupervisedConstraint(
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{
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"dataset": {
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"name": "DeepONetArrayDataset",
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"name": "ChipHeatDataset",
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"input": top_data,
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"label": label,
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"index": index,
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down_sup_constraint = ppsci.constraint.SupervisedConstraint(
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{
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"dataset": {
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"name": "DeepONetArrayDataset",
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"name": "ChipHeatDataset",
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"input": down_data,
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"label": label,
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"index": index,
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left_sup_constraint = ppsci.constraint.SupervisedConstraint(
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{
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"dataset": {
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"name": "DeepONetArrayDataset",
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"name": "ChipHeatDataset",
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"input": left_data,
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"label": label,
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"index": index,
@@ -318,7 +318,7 @@ def train(cfg: DictConfig):
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right_sup_constraint = ppsci.constraint.SupervisedConstraint(
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{
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"dataset": {
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"name": "DeepONetArrayDataset",
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"name": "ChipHeatDataset",
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"input": right_data,
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"label": label,
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"index": index,
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interior_sup_constraint = ppsci.constraint.SupervisedConstraint(
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{
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"dataset": {
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"name": "DeepONetArrayDataset",
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"name": "ChipHeatDataset",
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"input": interior_data,
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"label": label,
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"index": index,
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}
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# set optimizer
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optimizer = ppsci.optimizer.Adam(cfg.TRAIN.learning_rate)((model,))
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optimizer = ppsci.optimizer.Adam(cfg.TRAIN.learning_rate)(model)
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# set validator
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top_down_label = {"chip": np.zeros([cfg.NL, 1], dtype="float32")}
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},
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},
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"batch_size": cfg.NL,
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"sampler": {
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"name": "BatchSampler",
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},
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},
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ppsci.loss.MSELoss("mean"),
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output_expr={"chip": lambda out: out["T"] - out["u_one"]},
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},
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},
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"batch_size": cfg.NL,
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"sampler": {
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"name": "BatchSampler",
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},
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},
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ppsci.loss.MSELoss("mean"),
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output_expr={"chip": lambda out: out["T"] - out["u_one"]},
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},
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},
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"batch_size": (cfg.NL - 2),
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"sampler": {
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"name": "BatchSampler",
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},
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},
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ppsci.loss.MSELoss("mean"),
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output_expr={"chip": lambda out: out["T"] - out["u_one"]},
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},
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},
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"batch_size": (cfg.NL - 2),
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"sampler": {
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"name": "BatchSampler",
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},
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},
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ppsci.loss.MSELoss("mean"),
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output_expr={"chip": lambda out: out["T"] - out["u_one"]},
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"label": interior_label,
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},
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"batch_size": cfg.TRAIN.batch_size,
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"sampler": {
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"name": "BatchSampler",
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},
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},
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ppsci.loss.MSELoss("mean"),
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output_expr={
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},
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},
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"batch_size": cfg.NL,
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"sampler": {
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"name": "BatchSampler",
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},
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},
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ppsci.loss.MSELoss("mean"),
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output_expr={"chip": lambda out: out["T"] - out["u_one"]},
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},
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},
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"batch_size": cfg.NL,
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"sampler": {
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"name": "BatchSampler",
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},
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},
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ppsci.loss.MSELoss("mean"),
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output_expr={"chip": lambda out: out["T"] - out["u_one"]},
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},
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},
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"batch_size": (cfg.NL - 2),
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"sampler": {
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"name": "BatchSampler",
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},
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},
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ppsci.loss.MSELoss("mean"),
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output_expr={"chip": lambda out: out["T"] - out["u_one"]},
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},
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},
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"batch_size": (cfg.NL - 2),
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"sampler": {
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"name": "BatchSampler",
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},
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},
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ppsci.loss.MSELoss("mean"),
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output_expr={"chip": lambda out: out["T"] - out["u_one"]},
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"label": interior_label,
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},
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"batch_size": cfg.TRAIN.batch_size,
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"sampler": {
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"name": "BatchSampler",
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},
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},
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ppsci.loss.MSELoss("mean"),
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output_expr={

‎examples/chip_heat_simulation/conf/chip_heat_simulation.yaml‎ renamed to ‎examples/chip_heat/conf/chip_heat.yaml‎

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hydra:
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run:
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# dynamic output directory according to running time and override name
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dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}/${hydra.job.override_dirname}
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dir: outputs_chip_heat/${now:%Y-%m-%d}/${now:%H-%M-%S}/${hydra.job.override_dirname}
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job:
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name: ${mode} # name of logfile
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chdir: false # keep current working direcotry unchanged
@@ -45,7 +45,7 @@ MODEL:
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BC_input_keys: ['bc_data']
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trunk_input_keys: ["x", "y"]
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output_keys: ["T"]
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num_loc: 324 #18*18
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num_loc: 324 # 18*18
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bctype_loc: 1
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BC_num_loc: 76
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num_features: 400

‎mkdocs.yml‎

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- Heat_Exchanger: zh/examples/heat_exchanger.md
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- Heat_PINN: zh/examples/heat_pinn.md
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- PhyGeoNet: zh/examples/phygeonet.md
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- Chip_heat_simulation: zh/examples/chip_heat_simulation.md
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- Chip_heat: zh/examples/chip_heat_simulation.md
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- 材料科学(AI for Material):
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- hPINNs: zh/examples/hpinns.md
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- 地球科学(AI for Earth Science):

‎ppsci/data/dataset/__init__.py‎

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from typing import TYPE_CHECKING
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from ppsci.data.dataset.airfoil_dataset import MeshAirfoilDataset
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from ppsci.data.dataset.array_dataset import DeepONetArrayDataset
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from ppsci.data.dataset.array_dataset import ChipHeatDataset
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from ppsci.data.dataset.array_dataset import IterableNamedArrayDataset
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from ppsci.data.dataset.array_dataset import NamedArrayDataset
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from ppsci.data.dataset.csv_dataset import CSVDataset
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from ppsci.data.dataset.csv_dataset import IterableCSVDataset
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from ppsci.data.dataset.cylinder_dataset import MeshCylinderDataset
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from ppsci.data.dataset.dgmr_dataset import DGMRDataset
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from ppsci.data.dataset.era5_dataset import ERA5Dataset
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from ppsci.data.dataset.era5_dataset import ERA5SampledDataset
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from ppsci.data.dataset.mat_dataset import IterableMatDataset
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__all__ = [
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"IterableNamedArrayDataset",
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"NamedArrayDataset",
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"DeepONetArrayDataset",
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"ChipHeatDataset",
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"CSVDataset",
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"IterableCSVDataset",
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"ERA5Dataset",
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"RadarDataset",
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"RosslerDataset",
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"VtuDataset",
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"DGMRDataset",
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"MeshAirfoilDataset",
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"MeshCylinderDataset",
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"build_dataset",

‎ppsci/data/dataset/array_dataset.py‎

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return 1
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class DeepONetArrayDataset(io.Dataset):
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"""DeepONetArrayDataset for data loading of multi-branch DeepONet model.
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class ChipHeatDataset(io.Dataset):
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"""ChipHeatDataset for data loading of multi-branch DeepONet model.
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Args:
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input (Dict[str, np.ndarray]): Input dict.
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>>> index = ('x', 'u', 'bc', 'bc_data')
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>>> data_type = 'u'
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>>> weight = {"u": np.random.randn(100, 1)}
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>>> dataset = ppsci.data.dataset.DeepONetArrayDataset(input, label, index, data_type, weight)
164+
>>> dataset = ppsci.data.dataset.ChipHeatDataset(input, label, index, data_type, weight)
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"""
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def __init__(

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