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Update export api to long term version #888

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Update export api to long term version #888

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84 changes: 41 additions & 43 deletions docs/source/sdk-bundled-io.md
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Original file line number Diff line number Diff line change
Expand Up @@ -67,15 +67,13 @@ Here is a flow highlighting how to generate a `BundledProgram` given a PyTorch m
```python

import torch
from executorch import exir
from torch.export import export

from executorch.bundled_program.config import BundledConfig
from executorch.bundled_program.core import create_bundled_program
from executorch.bundled_program.serialize import serialize_from_bundled_program_to_flatbuffer
from executorch.bundled_program.serialize import deserialize_from_flatbuffer_to_bundled_program


from executorch.exir import ExecutorchBackendConfig
from executorch.exir.passes import MemoryPlanningPass, ToOutVarPass
from executorch.exir import to_edge


# Step 1: ExecuTorch Program Export
Expand Down Expand Up @@ -118,13 +116,14 @@ capture_inputs = {
for m_name in method_names
}

# Trace to FX Graph and emit the program
program = (
exir.capture_multiple(model, capture_inputs)
.to_edge()
.to_executorch()
.program
)
# Find each method of model needs to be traced my its name, export its FX Graph.
method_graphs = {
m_name: export(getattr(model, m_name), capture_inputs[m_name])
for m_name in method_names
}

# Emit the traced methods into ET Program.
program = to_edge(method_graphs).to_executorch().executorch_program

# Step 2: Construct BundledConfig

Expand Down Expand Up @@ -291,12 +290,13 @@ Here's the example of the dtype of test input not meet model's requirement:

```python
import torch
from executorch import exir
from executorch.exir import ExecutorchBackendConfig
from executorch.exir.passes import MemoryPlanningPass, ToOutVarPass
from torch.export import export

from executorch.bundled_program.config import BundledConfig
from executorch.bundled_program.core import create_bundled_program

from executorch.exir import to_edge


class Module(torch.nn.Module):
def __init__(self):
Expand All @@ -318,16 +318,14 @@ method_names = ['forward']
inputs = torch.ones(2, 2, dtype=torch.float)
print(model(inputs))

# Trace to FX Graph.
program = (
exir.capture(model, (inputs,))
.to_edge()
.to_executorch(
config=ExecutorchBackendConfig(
memory_planning_pass=MemoryPlanningPass(), to_out_var_pass=ToOutVarPass()
)
).program
)
# Find each method of model needs to be traced my its name, export its FX Graph.
method_graphs = {
m_name: export(getattr(model, m_name), (inputs, ))
for m_name in method_names
}

# Emit the traced methods into ET Program.
program = to_edge(method_graphs).to_executorch().executorch_program


# number of input sets to be verified
Expand Down Expand Up @@ -416,12 +414,13 @@ Another common error would be the method name in `BundledConfig` does not exist

```python
import torch
from executorch import exir
from executorch.exir import ExecutorchBackendConfig
from executorch.exir.passes import MemoryPlanningPass, ToOutVarPass
from torch.export import export

from executorch.bundled_program.config import BundledConfig
from executorch.bundled_program.core import create_bundled_program

from executorch.exir import to_edge



class Module(torch.nn.Module):
Expand All @@ -440,23 +439,18 @@ class Module(torch.nn.Module):

model = Module()

# NOTE: wrong_forward is not an inference method in the above model.
method_names = ['wrong_forward']
method_names = ['forward']

inputs = torch.ones(2, 2, dtype=torch.float)
print(model(inputs))

# Trace to FX Graph.
program = (
exir.capture(model, (inputs,))
.to_edge()
.to_executorch(
config=ExecutorchBackendConfig(
memory_planning_pass=MemoryPlanningPass(), to_out_var_pass=ToOutVarPass()
)
).program
)
# Find each method of model needs to be traced my its name, export its FX Graph.
method_graphs = {
m_name: export(getattr(model, m_name), (inputs, ))
for m_name in method_names
}

# Emit the traced methods into ET Program.
program = to_edge(method_graphs).to_executorch().executorch_program

# Number of input sets to be verified
n_input = 10
Expand All @@ -476,7 +470,11 @@ expected_outpus = [
[[model(*x)] for x in inputs[0]]
]

bundled_config = BundledConfig(method_names, inputs, expected_outpus)

# NOTE: MISSING_METHOD_NAME is not an inference method in the above model.
wrong_method_names = ['MISSING_METHOD_NAME']

bundled_config = BundledConfig(wrong_method_names, inputs, expected_outpus)

bundled_program = create_bundled_program(program, bundled_config)

Expand Down Expand Up @@ -518,6 +516,6 @@ File /executorch/bundled_program/core.py:147, in assert_valid_bundle(program, bu
150 but {str(method_name_of_bundled_config - method_name_of_program)} does not include."
152 # check if has been sorted in ascending alphabetical order of method name.
153 for bp_plan_id in range(1, len(bundled_config.execution_plan_tests)):
AssertionError: All method names in bundled config should be found in program.execution_plan, but {'wrong_forward'} does not include.
AssertionError: All method names in bundled config should be found in program.execution_plan, but {'MISSING_METHOD_NAME'} does not include.
```
:::