Python class
Graph
Graph
class max.graph.Graph(name: str, forward: Callable  None = None, input_types: Iterable[Type] = (), *args, **kwargs)
Represents a single MAX graph.
A Graph is a callable routine in MAX Engine. Like functions, graphs have a name and signature. Unlike a function, which follows an imperative programming model, a Graph follows a dataflow programming model, using lazilyexecuted, parallel operations instead of sequential instructions.
When you instantiate a graph, you must specify the input shapes as one or more TensorType or ListType values. Then, build a sequence of ops and set the graph output with output(). For example:
from dataclasses import dataclass
import numpy as np
from max.dtype import DType
from max.graph import Graph, TensorValue, TensorType
@dataclass
class Linear:
weight: np.ndarray
bias: np.ndarray
def __call__(self, x: TensorValue) > TensorValue:
return x @ self.weight + self.bias
linear_graph = Graph(
"linear",
Linear(np.ones((2, 2)), np.ones((2,))),
input_types=[TensorType(DType.float32, (2,))],
)
from dataclasses import dataclass
import numpy as np
from max.dtype import DType
from max.graph import Graph, TensorValue, TensorType
@dataclass
class Linear:
weight: np.ndarray
bias: np.ndarray
def __call__(self, x: TensorValue) > TensorValue:
return x @ self.weight + self.bias
linear_graph = Graph(
"linear",
Linear(np.ones((2, 2)), np.ones((2,))),
input_types=[TensorType(DType.float32, (2,))],
)
You can’t call a Graph directly from Python. You must compile it and execute it with MAX Engine. For more detail, see the tutorial about how to build a graph with MAX Graph.
add_weight()
add_weight(name: str, dtype: DType  None = None, shape: Iterable[int  str  Dim  integer]  None = None, filepath: PathLike  str  None = None, offset: int  None = None, quantization_encoding: QuantizationEncoding  None = None) → Weight
Initializes a new weight in the current graph.

Parameters:
 name – The name of this weight. All weights in a graph must have unique names.
 dtype – The DType of the weight. Defaults to Float32.
 shape – The shape of the weight. Defaults to a scalar (shape=[1]).
 filepath – File pointing to file containing weight value.
 offset – Offset to weight in the file (defaults to 0).
 quantization_encoding – Quantization encoding of the weight. Defaults to notquantized.

Returns:
The added Weight object.

Raises:
 ValueError if a weight with the same name already exists in the –
 graph. –
current
current
inputs
inputs*: tuple[max.graph.value.Value, ...]*
output()
unique_symbolic_dim()
unique_symbolic_dim(tag: str) → SymbolicDim
Create a new symbolic dim with a different name from any other.

Parameters:
tag – An additional identifier to help identify the dimension for debugging purposes.
Returns: The dimension.
weights
weights*: dict[str, max.graph.weight.Weight]*
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