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Types

#include "max/c/types.h"

Typedefs:

M_Status​

typedef struct M_Status M_Status

Contains the success or failure of an API call.

In general, any API that may fail accepts a M_Status argument that is filled in with a meaningful error message on failure.

You can create this with M_newStatus(). When you’re done, call M_freeStatus().

M_RuntimeConfig​

typedef struct M_RuntimeConfig M_RuntimeConfig

Specifies the MAX Engine configuration.

Configuration properties include the number of threads, artifact path, etc.

You can create this with M_newRuntimeConfig(). When you’re done, call M_freeRuntimeConfig().

M_RuntimeContext​

typedef struct M_RuntimeContext M_RuntimeContext

Contains information that needs to be shared between APIs.

You can create this with M_newRuntimeContext(). When you’re done, call M_freeRuntimeContext().

M_CompileConfig​

typedef struct M_CompileConfig M_CompileConfig

Specifies the configuration required for model compilation.

You can create this with M_newCompileConfig(). When you’re done, call M_freeCompileConfig().

M_AsyncCompiledModel​

typedef struct M_AsyncCompiledModel M_AsyncCompiledModel

Contains an async value to a compiled model.

M_AsyncCompiledModel can be passed to other APIs that accept compiled models as a function parameter. This async value will eventually resolve to a compiled model or an error in the case of compilation failure.

You can create this with M_compileModel(). When you’re done, call M_freeCompiledModel().

M_AsyncModel​

typedef struct M_AsyncModel M_AsyncModel

Contains a future used for inference.

The future will resolve to a model that’s ready for inference.

You can create this with M_initModel(). When you’re done, call M_freeModel().

M_AsyncTensor​

typedef struct M_AsyncTensor M_AsyncTensor

Contains an async value to a tensor for inference.

You can get this from M_getTensorByNameFrom(). When you’re done, call M_freeTensor().

M_TensorNameArray​

typedef struct M_TensorNameArray M_TensorNameArray

Contains an array of tensor names of model inputs or outputs.

You can get this from M_getInputNames() and M_getOutputNames(). When you’re done, call M_freeTensorNameArray().

M_TensorSpec​

typedef struct M_TensorSpec M_TensorSpec

Contains the representation of a shape and an element type.

You can create this with M_newTensorSpec(). When you’re done, call M_freeTensorSpec().

M_AsyncTensorMap​

typedef struct M_AsyncTensorMap M_AsyncTensorMap

Contains a collection of tensors.

The collection of tensors is used to represent inputs and outputs when executing a model.

You can create this with M_newAsyncTensorMap(). When you’re done, call M_freeAsyncTensorMap().

M_WeightsRegistry​

typedef struct M_WeightsRegistry M_WeightsRegistry

Maps unique weight names to their backing data.

You can create this with M_newWeightsRegistry(). When you’re done, call M_freeWeightsRegistry().

M_Device​

typedef struct M_Device M_Device

Contains a device handle.

A device represents a computational unit (CPU or GPU) that can execute operations and hold tensors.

You can create this with M_newDevice(). When you’re done, call M_freeDevice().

Enums:

M_Dtype​

enum M_Dtype

Represents all data types supported by the framework.

Values:

M_UNKNOWN​

enumerator M_UNKNOWN

mIsInteger​

enumerator mIsInteger

mIsFloat​

enumerator mIsFloat

mIsComplex​

enumerator mIsComplex

mIsSigned​

enumerator mIsSigned

Bit 0 encodes “isSigned”.

kIntWidthShift​

enumerator kIntWidthShift

M_INT1​

enumerator M_INT1

M_UINT1​

enumerator M_UINT1

M_INT2​

enumerator M_INT2

M_UINT2​

enumerator M_UINT2

M_INT4​

enumerator M_INT4

M_UINT4​

enumerator M_UINT4

M_INT8​

enumerator M_INT8

M_UINT8​

enumerator M_UINT8

M_INT16​

enumerator M_INT16

M_UINT16​

enumerator M_UINT16

M_INT32​

enumerator M_INT32

M_UINT32​

enumerator M_UINT32

M_INT64​

enumerator M_INT64

M_UINT64​

enumerator M_UINT64

M_INT128​

enumerator M_INT128

M_UINT128​

enumerator M_UINT128

M_FLOAT4_E2M1FN​

enumerator M_FLOAT4_E2M1FN

Bits 0 through 3 indicate the kind of FP value.

M_FLOAT8_E8M0FNU​

enumerator M_FLOAT8_E8M0FNU

Some slots are left blank here to enable us to support more lower precision types in the future.

M_FLOAT8_E3M4​

enumerator M_FLOAT8_E3M4

M_FLOAT8_E4M3FN​

enumerator M_FLOAT8_E4M3FN

M_FLOAT8_E4M3FNUZ​

enumerator M_FLOAT8_E4M3FNUZ

M_FLOAT8_E5M2​

enumerator M_FLOAT8_E5M2

M_FLOAT8_E5M2FNUZ​

enumerator M_FLOAT8_E5M2FNUZ

M_FLOAT16​

enumerator M_FLOAT16

M_BFLOAT16​

enumerator M_BFLOAT16

M_FLOAT32​

enumerator M_FLOAT32

M_FLOAT64​

enumerator M_FLOAT64

M_BOOL​

enumerator M_BOOL

M_AllocatorType​

enum M_AllocatorType

Contains an AllocatorType. You can choose between kCaching and kSystem kCaching trades off higher memory usage for better performance. kSystem uses the default system allocator.

Values:

kSystem​

enumerator kSystem

kCaching​

enumerator kCaching

M_ValueType​

enum M_ValueType

Represents the type of a value.

Values:

M_STRING_VALUE​

enumerator M_STRING_VALUE

M_DOUBLE_VALUE​

enumerator M_DOUBLE_VALUE

M_LONG_VALUE​

enumerator M_LONG_VALUE

M_BOOL_VALUE​

enumerator M_BOOL_VALUE

M_TENSOR_VALUE​

enumerator M_TENSOR_VALUE

M_LIST_VALUE​

enumerator M_LIST_VALUE

M_TUPLE_VALUE​

enumerator M_TUPLE_VALUE

M_DICT_VALUE​

enumerator M_DICT_VALUE

M_NONE_VALUE​

enumerator M_NONE_VALUE

M_UNKNOWN_VALUE​

enumerator M_UNKNOWN_VALUE

M_MOJO_VALUE​

enumerator M_MOJO_VALUE

M_PYTHON_MOJO_VALUE​

enumerator M_PYTHON_MOJO_VALUE

M_DeviceType​

enum M_DeviceType

Represents the type of device.

Values:

M_HOST​

enumerator M_HOST

M_ACCELERATOR​

enumerator M_ACCELERATOR

M_ResultOutputStyle​

enum M_ResultOutputStyle

Represents the result output style for debug printing.

Values:

M_COMPACT​

enumerator M_COMPACT

M_FULL​

enumerator M_FULL

M_BINARY​

enumerator M_BINARY

M_BINARY_MAX_CHECKPOINT​

enumerator M_BINARY_MAX_CHECKPOINT

M_NONE​

enumerator M_NONE

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