Struct NDArrayMatrixMultiplication

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pub struct NDArrayMatrixMultiplication { /* private fields */ }

Expand description

Wraps MPSNDArrayMatrixMultiplication.

Implementations§

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impl NDArrayMatrixMultiplication

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pub const fn as_ptr(&self) -> *mut c_void

Returns the retained Objective-C pointer backing this wrapper.

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impl NDArrayMatrixMultiplication

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pub fn new(device: &MetalDevice, source_count: usize) -> Option<Self>

Wraps a constructor on MPSNDArrayMatrixMultiplication.

Examples found in repository ?

examples/06_ndarray_matrix_multiplication.rs (line 51)

30fn main() {
31    let device = MetalDevice::system_default().expect("no Metal device available");
32    let queue = device.new_command_queue().expect("command queue");
33
34    let descriptor = NDArrayDescriptor::with_dimension_sizes(data_type::FLOAT32, &[2, 2, 1, 1])
35        .expect("descriptor");
36    let template = NDArray::new(&device, &descriptor).expect("template ndarray");
37    let byte_len = template.resource_size();
38    let rows = descriptor.length_of_dimension(1);
39    let row_stride_floats = byte_len / core::mem::size_of::<f32>() / rows;
40    let left_buffer =
41        buffer_with_f32_values_padded(&device, &[1.0, 2.0, 0.0, 0.0, 3.0, 4.0, 0.0, 0.0], byte_len);
42    let right_buffer =
43        buffer_with_f32_values_padded(&device, &[5.0, 6.0, 0.0, 0.0, 7.0, 8.0, 0.0, 0.0], byte_len);
44    let destination_buffer = buffer_with_f32_values_padded(&device, &[0.0; 8], byte_len);
45
46    let left = NDArray::new_with_buffer(&left_buffer, 0, &descriptor).expect("left ndarray");
47    let right = NDArray::new_with_buffer(&right_buffer, 0, &descriptor).expect("right ndarray");
48    let destination =
49        NDArray::new_with_buffer(&destination_buffer, 0, &descriptor).expect("destination ndarray");
50
51    let kernel = NDArrayMatrixMultiplication::new(&device, 2).expect("ndarray matmul");
52    kernel.set_alpha(1.0);
53    kernel.set_beta(0.0);
54
55    let command_buffer = queue.new_command_buffer().expect("command buffer");
56    kernel.encode_to_destination(&command_buffer, &[&left, &right], &destination);
57    command_buffer.commit();
58    command_buffer.wait_until_completed();
59
60    let padded_output = read_f32_values(&destination_buffer, row_stride_floats * rows);
61    let output = [
62        padded_output[0],
63        padded_output[1],
64        padded_output[row_stride_floats],
65        padded_output[row_stride_floats + 1],
66    ];
67    println!("{output:?}");
68}

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pub fn alpha(&self) -> f64

Wraps the corresponding MPSNDArrayMatrixMultiplication method.

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pub fn set_alpha(&self, alpha: f64)

Wraps the corresponding MPSNDArrayMatrixMultiplication setter.

Examples found in repository ?

examples/06_ndarray_matrix_multiplication.rs (line 52)

30fn main() {
31    let device = MetalDevice::system_default().expect("no Metal device available");
32    let queue = device.new_command_queue().expect("command queue");
33
34    let descriptor = NDArrayDescriptor::with_dimension_sizes(data_type::FLOAT32, &[2, 2, 1, 1])
35        .expect("descriptor");
36    let template = NDArray::new(&device, &descriptor).expect("template ndarray");
37    let byte_len = template.resource_size();
38    let rows = descriptor.length_of_dimension(1);
39    let row_stride_floats = byte_len / core::mem::size_of::<f32>() / rows;
40    let left_buffer =
41        buffer_with_f32_values_padded(&device, &[1.0, 2.0, 0.0, 0.0, 3.0, 4.0, 0.0, 0.0], byte_len);
42    let right_buffer =
43        buffer_with_f32_values_padded(&device, &[5.0, 6.0, 0.0, 0.0, 7.0, 8.0, 0.0, 0.0], byte_len);
44    let destination_buffer = buffer_with_f32_values_padded(&device, &[0.0; 8], byte_len);
45
46    let left = NDArray::new_with_buffer(&left_buffer, 0, &descriptor).expect("left ndarray");
47    let right = NDArray::new_with_buffer(&right_buffer, 0, &descriptor).expect("right ndarray");
48    let destination =
49        NDArray::new_with_buffer(&destination_buffer, 0, &descriptor).expect("destination ndarray");
50
51    let kernel = NDArrayMatrixMultiplication::new(&device, 2).expect("ndarray matmul");
52    kernel.set_alpha(1.0);
53    kernel.set_beta(0.0);
54
55    let command_buffer = queue.new_command_buffer().expect("command buffer");
56    kernel.encode_to_destination(&command_buffer, &[&left, &right], &destination);
57    command_buffer.commit();
58    command_buffer.wait_until_completed();
59
60    let padded_output = read_f32_values(&destination_buffer, row_stride_floats * rows);
61    let output = [
62        padded_output[0],
63        padded_output[1],
64        padded_output[row_stride_floats],
65        padded_output[row_stride_floats + 1],
66    ];
67    println!("{output:?}");
68}

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pub fn beta(&self) -> f64

Wraps the corresponding MPSNDArrayMatrixMultiplication method.

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pub fn set_beta(&self, beta: f64)

Wraps the corresponding MPSNDArrayMatrixMultiplication setter.

Examples found in repository ?

examples/06_ndarray_matrix_multiplication.rs (line 53)

30fn main() {
31    let device = MetalDevice::system_default().expect("no Metal device available");
32    let queue = device.new_command_queue().expect("command queue");
33
34    let descriptor = NDArrayDescriptor::with_dimension_sizes(data_type::FLOAT32, &[2, 2, 1, 1])
35        .expect("descriptor");
36    let template = NDArray::new(&device, &descriptor).expect("template ndarray");
37    let byte_len = template.resource_size();
38    let rows = descriptor.length_of_dimension(1);
39    let row_stride_floats = byte_len / core::mem::size_of::<f32>() / rows;
40    let left_buffer =
41        buffer_with_f32_values_padded(&device, &[1.0, 2.0, 0.0, 0.0, 3.0, 4.0, 0.0, 0.0], byte_len);
42    let right_buffer =
43        buffer_with_f32_values_padded(&device, &[5.0, 6.0, 0.0, 0.0, 7.0, 8.0, 0.0, 0.0], byte_len);
44    let destination_buffer = buffer_with_f32_values_padded(&device, &[0.0; 8], byte_len);
45
46    let left = NDArray::new_with_buffer(&left_buffer, 0, &descriptor).expect("left ndarray");
47    let right = NDArray::new_with_buffer(&right_buffer, 0, &descriptor).expect("right ndarray");
48    let destination =
49        NDArray::new_with_buffer(&destination_buffer, 0, &descriptor).expect("destination ndarray");
50
51    let kernel = NDArrayMatrixMultiplication::new(&device, 2).expect("ndarray matmul");
52    kernel.set_alpha(1.0);
53    kernel.set_beta(0.0);
54
55    let command_buffer = queue.new_command_buffer().expect("command buffer");
56    kernel.encode_to_destination(&command_buffer, &[&left, &right], &destination);
57    command_buffer.commit();
58    command_buffer.wait_until_completed();
59
60    let padded_output = read_f32_values(&destination_buffer, row_stride_floats * rows);
61    let output = [
62        padded_output[0],
63        padded_output[1],
64        padded_output[row_stride_floats],
65        padded_output[row_stride_floats + 1],
66    ];
67    println!("{output:?}");
68}

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pub fn encode( &self, command_buffer: &MetalCommandBuffer, source_arrays: &[&NDArray], ) -> Option<NDArray>

Wraps the corresponding MPSNDArrayMatrixMultiplication encode entry point.

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pub fn encode_to_destination( &self, command_buffer: &MetalCommandBuffer, source_arrays: &[&NDArray], destination: &NDArray, )

Wraps the corresponding MPSNDArrayMatrixMultiplication encode entry point.

Examples found in repository ?

examples/06_ndarray_matrix_multiplication.rs (line 56)

30fn main() {
31    let device = MetalDevice::system_default().expect("no Metal device available");
32    let queue = device.new_command_queue().expect("command queue");
33
34    let descriptor = NDArrayDescriptor::with_dimension_sizes(data_type::FLOAT32, &[2, 2, 1, 1])
35        .expect("descriptor");
36    let template = NDArray::new(&device, &descriptor).expect("template ndarray");
37    let byte_len = template.resource_size();
38    let rows = descriptor.length_of_dimension(1);
39    let row_stride_floats = byte_len / core::mem::size_of::<f32>() / rows;
40    let left_buffer =
41        buffer_with_f32_values_padded(&device, &[1.0, 2.0, 0.0, 0.0, 3.0, 4.0, 0.0, 0.0], byte_len);
42    let right_buffer =
43        buffer_with_f32_values_padded(&device, &[5.0, 6.0, 0.0, 0.0, 7.0, 8.0, 0.0, 0.0], byte_len);
44    let destination_buffer = buffer_with_f32_values_padded(&device, &[0.0; 8], byte_len);
45
46    let left = NDArray::new_with_buffer(&left_buffer, 0, &descriptor).expect("left ndarray");
47    let right = NDArray::new_with_buffer(&right_buffer, 0, &descriptor).expect("right ndarray");
48    let destination =
49        NDArray::new_with_buffer(&destination_buffer, 0, &descriptor).expect("destination ndarray");
50
51    let kernel = NDArrayMatrixMultiplication::new(&device, 2).expect("ndarray matmul");
52    kernel.set_alpha(1.0);
53    kernel.set_beta(0.0);
54
55    let command_buffer = queue.new_command_buffer().expect("command buffer");
56    kernel.encode_to_destination(&command_buffer, &[&left, &right], &destination);
57    command_buffer.commit();
58    command_buffer.wait_until_completed();
59
60    let padded_output = read_f32_values(&destination_buffer, row_stride_floats * rows);
61    let output = [
62        padded_output[0],
63        padded_output[1],
64        padded_output[row_stride_floats],
65        padded_output[row_stride_floats + 1],
66    ];
67    println!("{output:?}");
68}