GstTensor
Hold tensor data
Members
id
		(GQuark)
		–
	semantically identify the contents of the tensor
layout
		(GstTensorLayout)
		–
	Indicate tensor layout
data_type
		(GstTensorDataType)
		–
	GstTensorDataType of tensor data
dims_order
		(GstTensorDimOrder)
		–
	Indicate tensor elements layout in memory.
num_dims
		(gsize)
		–
	number of tensor dimensions
dims
		(gsize *)
		–
	number of tensor dimensions
Since : 1.26
GstAnalytics.Tensor
Hold tensor data
Members
id
		(GLib.Quark)
		–
	semantically identify the contents of the tensor
layout
		(GstAnalytics.TensorLayout)
		–
	Indicate tensor layout
data_type
		(GstAnalytics.TensorDataType)
		–
	GstAnalytics.TensorDataType of tensor data
data
		(Gst.Buffer)
		–
	Gst.Buffer holding tensor data
dims_order
		(GstAnalytics.TensorDimOrder)
		–
	Indicate tensor elements layout in memory.
num_dims
		(Number)
		–
	number of tensor dimensions
dims
		([ Number ])
		–
	number of tensor dimensions
Since : 1.26
GstAnalytics.Tensor
Hold tensor data
Members
id
		(GLib.Quark)
		–
	semantically identify the contents of the tensor
layout
		(GstAnalytics.TensorLayout)
		–
	Indicate tensor layout
data_type
		(GstAnalytics.TensorDataType)
		–
	GstAnalytics.TensorDataType of tensor data
data
		(Gst.Buffer)
		–
	Gst.Buffer holding tensor data
dims_order
		(GstAnalytics.TensorDimOrder)
		–
	Indicate tensor elements layout in memory.
num_dims
		(int)
		–
	number of tensor dimensions
dims
		([ int ])
		–
	number of tensor dimensions
Since : 1.26
Constructors
gst_tensor_alloc
GstTensor * gst_tensor_alloc (gsize num_dims)
Allocate a tensor with num_dims dimensions.
Parameters:
num_dims
–
Number of dimension of the tensors
tensor allocated
Since : 1.26
GstAnalytics.Tensor.prototype.alloc
function GstAnalytics.Tensor.prototype.alloc(num_dims: Number): {
    // javascript wrapper for 'gst_tensor_alloc'
}
Allocate a tensor with num_dims dimensions.
Parameters:
Number of dimension of the tensors
tensor allocated
Since : 1.26
GstAnalytics.Tensor.alloc
def GstAnalytics.Tensor.alloc (num_dims):
    #python wrapper for 'gst_tensor_alloc'
Allocate a tensor with num_dims dimensions.
Parameters:
Number of dimension of the tensors
tensor allocated
Since : 1.26
gst_tensor_new_simple
GstTensor * gst_tensor_new_simple (GQuark id, GstTensorDataType data_type, GstBuffer * data, GstTensorDimOrder dims_order, gsize num_dims, gsize * dims)
Allocates a new GstTensor of dims_order ROW_MAJOR or COLUMN_MAJOR and with an interleaved layout
Parameters:
id
–
semantically identify the contents of the tensor
data_type
–
GstTensorDataType of tensor data
data
(
[transfer: full])
–
GstBuffer holding tensor data
dims_order
–
Indicate tensor dimension indexing order
num_dims
–
number of tensor dimensions
dims
(
[array length=num_dims])
–
tensor dimensions. Value of 0 mean the dimension is dynamic.
A newly allocated GstTensor
Since : 1.26
GstAnalytics.Tensor.prototype.new_simple
function GstAnalytics.Tensor.prototype.new_simple(id: GLib.Quark, data_type: GstAnalytics.TensorDataType, data: Gst.Buffer, dims_order: GstAnalytics.TensorDimOrder, num_dims: Number, dims: [ Number ]): {
    // javascript wrapper for 'gst_tensor_new_simple'
}
Allocates a new GstAnalytics.Tensor of dims_order ROW_MAJOR or COLUMN_MAJOR and with an interleaved layout
Parameters:
semantically identify the contents of the tensor
GstAnalytics.TensorDataType of tensor data
Gst.Buffer holding tensor data
Indicate tensor dimension indexing order
number of tensor dimensions
tensor dimensions. Value of 0 mean the dimension is dynamic.
A newly allocated GstAnalytics.Tensor
Since : 1.26
GstAnalytics.Tensor.new_simple
def GstAnalytics.Tensor.new_simple (id, data_type, data, dims_order, num_dims, dims):
    #python wrapper for 'gst_tensor_new_simple'
Allocates a new GstAnalytics.Tensor of dims_order ROW_MAJOR or COLUMN_MAJOR and with an interleaved layout
Parameters:
semantically identify the contents of the tensor
GstAnalytics.TensorDataType of tensor data
Gst.Buffer holding tensor data
Indicate tensor dimension indexing order
number of tensor dimensions
tensor dimensions. Value of 0 mean the dimension is dynamic.
A newly allocated GstAnalytics.Tensor
Since : 1.26
Methods
gst_tensor_copy
GstTensor * gst_tensor_copy (const GstTensor * tensor)
Create a copy of tensor.
Parameters:
tensor
(
[transfer: none][nullable])
–
a GstTensor to be copied
a new GstTensor
Since : 1.26
GstAnalytics.Tensor.prototype.copy
function GstAnalytics.Tensor.prototype.copy(): {
    // javascript wrapper for 'gst_tensor_copy'
}
Create a copy of tensor.
Parameters:
a GstAnalytics.Tensor to be copied
a new GstAnalytics.Tensor
Since : 1.26
GstAnalytics.Tensor.copy
def GstAnalytics.Tensor.copy (self):
    #python wrapper for 'gst_tensor_copy'
Create a copy of tensor.
Parameters:
a GstAnalytics.Tensor to be copied
a new GstAnalytics.Tensor
Since : 1.26
gst_tensor_free
gst_tensor_free (GstTensor * tensor)
Free tensor
Parameters:
tensor
(
[in][transfer: full])
–
pointer to tensor to free
Since : 1.26
GstAnalytics.Tensor.prototype.free
function GstAnalytics.Tensor.prototype.free(): {
    // javascript wrapper for 'gst_tensor_free'
}
Free tensor
Parameters:
pointer to tensor to free
Since : 1.26
GstAnalytics.Tensor.free
def GstAnalytics.Tensor.free (self):
    #python wrapper for 'gst_tensor_free'
Free tensor
Parameters:
pointer to tensor to free
Since : 1.26
gst_tensor_get_dims
gsize * gst_tensor_get_dims (GstTensor * tensor, gsize * num_dims)
Gets the dimensions of the tensor.
The dims array form the tensor
Since : 1.26
GstAnalytics.Tensor.prototype.get_dims
function GstAnalytics.Tensor.prototype.get_dims(): {
    // javascript wrapper for 'gst_tensor_get_dims'
}
Gets the dimensions of the tensor.
Parameters:
Returns a tuple made of:
The dims array form the tensor
The dims array form the tensor
Since : 1.26
GstAnalytics.Tensor.get_dims
def GstAnalytics.Tensor.get_dims (self):
    #python wrapper for 'gst_tensor_get_dims'
Gets the dimensions of the tensor.
Parameters:
Returns a tuple made of:
The dims array form the tensor
The dims array form the tensor
Since : 1.26
Enumerations
GstTensorDataType
Describe the type of data contain in the tensor.
Members
GST_TENSOR_DATA_TYPE_INT4
		(0)
		–
	signed 4 bit integer tensor data
GST_TENSOR_DATA_TYPE_INT8
		(1)
		–
	signed 8 bit integer tensor data
GST_TENSOR_DATA_TYPE_INT16
		(2)
		–
	signed 16 bit integer tensor data
GST_TENSOR_DATA_TYPE_INT32
		(3)
		–
	signed 32 bit integer tensor data
GST_TENSOR_DATA_TYPE_INT64
		(4)
		–
	signed 64 bit integer tensor data
GST_TENSOR_DATA_TYPE_UINT4
		(5)
		–
	unsigned 4 bit integer tensor data
GST_TENSOR_DATA_TYPE_UINT8
		(6)
		–
	unsigned 8 bit integer tensor data
GST_TENSOR_DATA_TYPE_UINT16
		(7)
		–
	unsigned 16 bit integer tensor data
GST_TENSOR_DATA_TYPE_UINT32
		(8)
		–
	unsigned 32 bit integer tensor data
GST_TENSOR_DATA_TYPE_UINT64
		(9)
		–
	unsigned 64 bit integer tensor data
GST_TENSOR_DATA_TYPE_FLOAT16
		(10)
		–
	16 bit floating point tensor data
GST_TENSOR_DATA_TYPE_FLOAT32
		(11)
		–
	32 bit floating point tensor data
GST_TENSOR_DATA_TYPE_FLOAT64
		(12)
		–
	64 bit floating point tensor data
GST_TENSOR_DATA_TYPE_BFLOAT16
		(13)
		–
	"brain" 16 bit floating point tensor data
Since : 1.26
GstAnalytics.TensorDataType
Describe the type of data contain in the tensor.
Members
GstAnalytics.TensorDataType.INT4
		(0)
		–
	signed 4 bit integer tensor data
GstAnalytics.TensorDataType.INT8
		(1)
		–
	signed 8 bit integer tensor data
GstAnalytics.TensorDataType.INT16
		(2)
		–
	signed 16 bit integer tensor data
GstAnalytics.TensorDataType.INT32
		(3)
		–
	signed 32 bit integer tensor data
GstAnalytics.TensorDataType.INT64
		(4)
		–
	signed 64 bit integer tensor data
GstAnalytics.TensorDataType.UINT4
		(5)
		–
	unsigned 4 bit integer tensor data
GstAnalytics.TensorDataType.UINT8
		(6)
		–
	unsigned 8 bit integer tensor data
GstAnalytics.TensorDataType.UINT16
		(7)
		–
	unsigned 16 bit integer tensor data
GstAnalytics.TensorDataType.UINT32
		(8)
		–
	unsigned 32 bit integer tensor data
GstAnalytics.TensorDataType.UINT64
		(9)
		–
	unsigned 64 bit integer tensor data
GstAnalytics.TensorDataType.FLOAT16
		(10)
		–
	16 bit floating point tensor data
GstAnalytics.TensorDataType.FLOAT32
		(11)
		–
	32 bit floating point tensor data
GstAnalytics.TensorDataType.FLOAT64
		(12)
		–
	64 bit floating point tensor data
GstAnalytics.TensorDataType.BFLOAT16
		(13)
		–
	"brain" 16 bit floating point tensor data
Since : 1.26
GstAnalytics.TensorDataType
Describe the type of data contain in the tensor.
Members
GstAnalytics.TensorDataType.INT4
		(0)
		–
	signed 4 bit integer tensor data
GstAnalytics.TensorDataType.INT8
		(1)
		–
	signed 8 bit integer tensor data
GstAnalytics.TensorDataType.INT16
		(2)
		–
	signed 16 bit integer tensor data
GstAnalytics.TensorDataType.INT32
		(3)
		–
	signed 32 bit integer tensor data
GstAnalytics.TensorDataType.INT64
		(4)
		–
	signed 64 bit integer tensor data
GstAnalytics.TensorDataType.UINT4
		(5)
		–
	unsigned 4 bit integer tensor data
GstAnalytics.TensorDataType.UINT8
		(6)
		–
	unsigned 8 bit integer tensor data
GstAnalytics.TensorDataType.UINT16
		(7)
		–
	unsigned 16 bit integer tensor data
GstAnalytics.TensorDataType.UINT32
		(8)
		–
	unsigned 32 bit integer tensor data
GstAnalytics.TensorDataType.UINT64
		(9)
		–
	unsigned 64 bit integer tensor data
GstAnalytics.TensorDataType.FLOAT16
		(10)
		–
	16 bit floating point tensor data
GstAnalytics.TensorDataType.FLOAT32
		(11)
		–
	32 bit floating point tensor data
GstAnalytics.TensorDataType.FLOAT64
		(12)
		–
	64 bit floating point tensor data
GstAnalytics.TensorDataType.BFLOAT16
		(13)
		–
	"brain" 16 bit floating point tensor data
Since : 1.26
GstTensorDimOrder
Indicate to read tensor from memory in row-major or column-major order.
Members
GST_TENSOR_DIM_ORDER_ROW_MAJOR
		(0)
		–
	elements along a row are consecutive in memory
GST_TENSOR_DIM_ORDER_COL_MAJOR
		(1)
		–
	elements along a column are consecutive in memory
Since : 1.26
GstAnalytics.TensorDimOrder
Indicate to read tensor from memory in row-major or column-major order.
Members
GstAnalytics.TensorDimOrder.ROW_MAJOR
		(0)
		–
	elements along a row are consecutive in memory
GstAnalytics.TensorDimOrder.COL_MAJOR
		(1)
		–
	elements along a column are consecutive in memory
Since : 1.26
GstAnalytics.TensorDimOrder
Indicate to read tensor from memory in row-major or column-major order.
Members
GstAnalytics.TensorDimOrder.ROW_MAJOR
		(0)
		–
	elements along a row are consecutive in memory
GstAnalytics.TensorDimOrder.COL_MAJOR
		(1)
		–
	elements along a column are consecutive in memory
Since : 1.26
GstTensorLayout
Indicate tensor storage in memory.
Members
GST_TENSOR_LAYOUT_CONTIGUOUS
		(0)
		–
	indicate the tensor is stored in a dense format in memory
Since : 1.26
GstAnalytics.TensorLayout
Indicate tensor storage in memory.
Members
GstAnalytics.TensorLayout.TENSOR_LAYOUT_CONTIGUOUS
		(0)
		–
	indicate the tensor is stored in a dense format in memory
Since : 1.26
GstAnalytics.TensorLayout
Indicate tensor storage in memory.
Members
GstAnalytics.TensorLayout.TENSOR_LAYOUT_CONTIGUOUS
		(0)
		–
	indicate the tensor is stored in a dense format in memory
Since : 1.26
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