CMSIS-NN
Version 1.2.0
CMSIS NN Software Library
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Functions | |
arm_status | arm_fully_connected_mat_q7_vec_q15 (const q15_t *pV, const q7_t *pM, const uint16_t dim_vec, const uint16_t num_of_rows, const uint16_t bias_shift, const uint16_t out_shift, const q7_t *bias, q15_t *pOut, q15_t *vec_buffer) |
Mixed Q15-Q7 fully-connected layer function. More... | |
arm_status | arm_fully_connected_mat_q7_vec_q15_opt (const q15_t *pV, const q7_t *pM, const uint16_t dim_vec, const uint16_t num_of_rows, const uint16_t bias_shift, const uint16_t out_shift, const q7_t *bias, q15_t *pOut, q15_t *vec_buffer) |
Mixed Q15-Q7 opt fully-connected layer function. More... | |
arm_status | arm_fully_connected_q15 (const q15_t *pV, const q15_t *pM, const uint16_t dim_vec, const uint16_t num_of_rows, const uint16_t bias_shift, const uint16_t out_shift, const q15_t *bias, q15_t *pOut, q15_t *vec_buffer) |
Q15 opt fully-connected layer function. More... | |
arm_status | arm_fully_connected_q15_opt (const q15_t *pV, const q15_t *pM, const uint16_t dim_vec, const uint16_t num_of_rows, const uint16_t bias_shift, const uint16_t out_shift, const q15_t *bias, q15_t *pOut, q15_t *vec_buffer) |
Q15 opt fully-connected layer function. More... | |
arm_status | arm_fully_connected_q7 (const q7_t *pV, const q7_t *pM, const uint16_t dim_vec, const uint16_t num_of_rows, const uint16_t bias_shift, const uint16_t out_shift, const q7_t *bias, q7_t *pOut, q15_t *vec_buffer) |
Q7 basic fully-connected layer function. More... | |
arm_status | arm_fully_connected_q7_opt (const q7_t *pV, const q7_t *pM, const uint16_t dim_vec, const uint16_t num_of_rows, const uint16_t bias_shift, const uint16_t out_shift, const q7_t *bias, q7_t *pOut, q15_t *vec_buffer) |
Q7 opt fully-connected layer function. More... | |
Perform fully-connected layer
Fully-connected layer is basically a matrix-vector multiplication with bias. The matrix is the weights and the input/output vectors are the activation values. Supported {weight, activation} precisions include {8-bit, 8-bit}, {16-bit, 16-bit}, and {8-bit, 16-bit}.
Here we have two types of kernel functions. The basic function implements the function using regular GEMV approach. The opt functions operates with weights in interleaved formats.
arm_status arm_fully_connected_mat_q7_vec_q15 | ( | const q15_t * | pV, |
const q7_t * | pM, | ||
const uint16_t | dim_vec, | ||
const uint16_t | num_of_rows, | ||
const uint16_t | bias_shift, | ||
const uint16_t | out_shift, | ||
const q7_t * | bias, | ||
q15_t * | pOut, | ||
q15_t * | vec_buffer | ||
) |
[in] | pV | pointer to input vector |
[in] | pM | pointer to matrix weights |
[in] | dim_vec | length of the vector |
[in] | num_of_rows | number of rows in weight matrix |
[in] | bias_shift | amount of left-shift for bias |
[in] | out_shift | amount of right-shift for output |
[in] | bias | pointer to bias |
[in,out] | pOut | pointer to output vector |
[in,out] | vec_buffer | pointer to buffer space for input |
ARM_MATH_SUCCESS
Buffer size:
vec_buffer size: 0
Q7_Q15 version of the fully connected layer
Weights are in q7_t and Activations are in q15_t
References NN_ROUND.
Referenced by gru_example().
arm_status arm_fully_connected_mat_q7_vec_q15_opt | ( | const q15_t * | pV, |
const q7_t * | pM, | ||
const uint16_t | dim_vec, | ||
const uint16_t | num_of_rows, | ||
const uint16_t | bias_shift, | ||
const uint16_t | out_shift, | ||
const q7_t * | bias, | ||
q15_t * | pOut, | ||
q15_t * | vec_buffer | ||
) |
[in] | pV | pointer to input vector |
[in] | pM | pointer to matrix weights |
[in] | dim_vec | length of the vector |
[in] | num_of_rows | number of rows in weight matrix |
[in] | bias_shift | amount of left-shift for bias |
[in] | out_shift | amount of right-shift for output |
[in] | bias | pointer to bias |
[in,out] | pOut | pointer to output vector |
[in,out] | vec_buffer | pointer to buffer space for input |
ARM_MATH_SUCCESS
Buffer size:
vec_buffer size: 0
Q7_Q15 version of the fully connected layer
Weights are in q7_t and Activations are in q15_t
Limitation: x4 version requires weight reordering to work
Here we use only one pointer to read 4 rows in the weight matrix. So if the original q7_t matrix looks like this:
| a11 | a12 | a13 | a14 | a15 | a16 | a17 |
| a21 | a22 | a23 | a24 | a25 | a26 | a27 |
| a31 | a32 | a33 | a34 | a35 | a36 | a37 |
| a41 | a42 | a43 | a44 | a45 | a46 | a47 |
| a51 | a52 | a53 | a54 | a55 | a56 | a57 |
| a61 | a62 | a63 | a64 | a65 | a66 | a67 |
We operates on multiple-of-4 rows, so the first four rows becomes
| a11 | a21 | a12 | a22 | a31 | a41 | a32 | a42 |
| a13 | a23 | a14 | a24 | a33 | a43 | a34 | a44 |
| a15 | a25 | a16 | a26 | a35 | a45 | a36 | a46 |
The column left over will be in-order. which is: | a17 | a27 | a37 | a47 |
For the left-over rows, we do 1x1 computation, so the data remains as its original order.
So the stored weight matrix looks like this:
| a11 | a21 | a12 | a22 | a31 | a41 |
| a32 | a42 | a13 | a23 | a14 | a24 |
| a33 | a43 | a34 | a44 | a15 | a25 |
| a16 | a26 | a35 | a45 | a36 | a46 |
| a17 | a27 | a37 | a47 | a51 | a52 |
| a53 | a54 | a55 | a56 | a57 | a61 |
| a62 | a63 | a64 | a65 | a66 | a67 |
References NN_ROUND.
Referenced by gru_example().
arm_status arm_fully_connected_q15 | ( | const q15_t * | pV, |
const q15_t * | pM, | ||
const uint16_t | dim_vec, | ||
const uint16_t | num_of_rows, | ||
const uint16_t | bias_shift, | ||
const uint16_t | out_shift, | ||
const q15_t * | bias, | ||
q15_t * | pOut, | ||
q15_t * | vec_buffer | ||
) |
Q15 basic fully-connected layer function.
[in] | pV | pointer to input vector |
[in] | pM | pointer to matrix weights |
[in] | dim_vec | length of the vector |
[in] | num_of_rows | number of rows in weight matrix |
[in] | bias_shift | amount of left-shift for bias |
[in] | out_shift | amount of right-shift for output |
[in] | bias | pointer to bias |
[in,out] | pOut | pointer to output vector |
[in,out] | vec_buffer | pointer to buffer space for input |
ARM_MATH_SUCCESS
Buffer size:
vec_buffer size: 0
References NN_ROUND.
arm_status arm_fully_connected_q15_opt | ( | const q15_t * | pV, |
const q15_t * | pM, | ||
const uint16_t | dim_vec, | ||
const uint16_t | num_of_rows, | ||
const uint16_t | bias_shift, | ||
const uint16_t | out_shift, | ||
const q15_t * | bias, | ||
q15_t * | pOut, | ||
q15_t * | vec_buffer | ||
) |
[in] | pV | pointer to input vector |
[in] | pM | pointer to matrix weights |
[in] | dim_vec | length of the vector |
[in] | num_of_rows | number of rows in weight matrix |
[in] | bias_shift | amount of left-shift for bias |
[in] | out_shift | amount of right-shift for output |
[in] | bias | pointer to bias |
[in,out] | pOut | pointer to output vector |
[in,out] | vec_buffer | pointer to buffer space for input |
ARM_MATH_SUCCESS
Buffer size:
vec_buffer size: 0
Here we use only one pointer to read 4 rows in the weight matrix. So if the original matrix looks like this:
| a11 | a12 | a13 |
| a21 | a22 | a23 |
| a31 | a32 | a33 |
| a41 | a42 | a43 |
| a51 | a52 | a53 |
| a61 | a62 | a63 |
We operates on multiple-of-4 rows, so the first four rows becomes
| a11 | a12 | a21 | a22 | a31 | a32 | a41 | a42 |
| a13 | a23 | a33 | a43 |
Remaining rows are kept the same original order.
So the stored weight matrix looks like this:
| a11 | a12 | a21 | a22 | a31 | a32 | a41 | a42 |
| a13 | a23 | a33 | a43 | a51 | a52 | a53 | a61 |
| a62 | a63 |
References NN_ROUND.
arm_status arm_fully_connected_q7 | ( | const q7_t * | pV, |
const q7_t * | pM, | ||
const uint16_t | dim_vec, | ||
const uint16_t | num_of_rows, | ||
const uint16_t | bias_shift, | ||
const uint16_t | out_shift, | ||
const q7_t * | bias, | ||
q7_t * | pOut, | ||
q15_t * | vec_buffer | ||
) |
[in] | pV | pointer to input vector |
[in] | pM | pointer to matrix weights |
[in] | dim_vec | length of the vector |
[in] | num_of_rows | number of rows in weight matrix |
[in] | bias_shift | amount of left-shift for bias |
[in] | out_shift | amount of right-shift for output |
[in] | bias | pointer to bias |
[in,out] | pOut | pointer to output vector |
[in,out] | vec_buffer | pointer to buffer space for input |
ARM_MATH_SUCCESS
Buffer size:
vec_buffer size: dim_vec
This basic function is designed to work with regular weight matrix without interleaving.
References arm_q7_to_q15_reordered_no_shift(), and NN_ROUND.
arm_status arm_fully_connected_q7_opt | ( | const q7_t * | pV, |
const q7_t * | pM, | ||
const uint16_t | dim_vec, | ||
const uint16_t | num_of_rows, | ||
const uint16_t | bias_shift, | ||
const uint16_t | out_shift, | ||
const q7_t * | bias, | ||
q7_t * | pOut, | ||
q15_t * | vec_buffer | ||
) |
[in] | pV | pointer to input vector |
[in] | pM | pointer to matrix weights |
[in] | dim_vec | length of the vector |
[in] | num_of_rows | number of rows in weight matrix |
[in] | bias_shift | amount of left-shift for bias |
[in] | out_shift | amount of right-shift for output |
[in] | bias | pointer to bias |
[in,out] | pOut | pointer to output vector |
[in,out] | vec_buffer | pointer to buffer space for input |
ARM_MATH_SUCCESS
Buffer size:
vec_buffer size: dim_vec
This opt function is designed to work with interleaved weight matrix. The vector input is assumed in q7_t format, we call arm_q7_to_q15_no_shift_shuffle function to expand into q15_t format with certain weight re-ordering, refer to the function comments for more details. Here we use only one pointer to read 4 rows in the weight matrix. So if the original q7_t matrix looks like this:
| a11 | a12 | a13 | a14 | a15 | a16 | a17 |
| a21 | a22 | a23 | a24 | a25 | a26 | a27 |
| a31 | a32 | a33 | a34 | a35 | a36 | a37 |
| a41 | a42 | a43 | a44 | a45 | a46 | a47 |
| a51 | a52 | a53 | a54 | a55 | a56 | a57 |
| a61 | a62 | a63 | a64 | a65 | a66 | a67 |
We operates on multiple-of-4 rows, so the first four rows becomes
| a11 | a21 | a13 | a23 | a31 | a41 | a33 | a43 |
| a12 | a22 | a14 | a24 | a32 | a42 | a34 | a44 |
| a15 | a25 | a35 | a45 | a16 | a26 | a36 | a46 |
So within the kernel, we first read the re-ordered vector in as:
| b1 | b3 | and | b2 | b4 |
the four q31_t weights will look like
| a11 | a13 |, | a21 | a23 |, | a31 | a33 |, | a41 | a43 |
| a12 | a14 |, | a22 | a24 |, | a32 | a34 |, | a42 | a44 |
The column left over will be in-order. which is:
| a17 | a27 | a37 | a47 |
For the left-over rows, we do 1x1 computation, so the data remains as its original order.
So the stored weight matrix looks like this:
| a11 | a21 | a13 | a23 | a31 | a41 |
| a33 | a43 | a12 | a22 | a14 | a24 |
| a32 | a42 | a34 | a44 | a15 | a25 |
| a35 | a45 | a16 | a26 | a36 | a46 |
| a17 | a27 | a37 | a47 | a51 | a52 |
| a53 | a54 | a55 | a56 | a57 | a61 |
| a62 | a63 | a64 | a65 | a66 | a67 |
References arm_q7_to_q15_reordered_no_shift(), and NN_ROUND.
Referenced by main().