add nnom pack and example

components/ai/nnom/src/layers/nnom_input.c

@@ -0,0 +1,145 @@
+/*
+ * Copyright (c) 2018-2020
+ * Jianjia Ma
+ * majianjia@live.com
+ *
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Change Logs:
+ * Date           Author       Notes
+ * 2019-07-23     Jianjia Ma   The first version
+ */
+
+#include <stdint.h>
+#include <string.h>
+#include <stdbool.h>
+
+#include "nnom.h"
+#include "nnom_local.h"
+#include "nnom_layers.h"
+#include "layers/nnom_input.h"
+
+nnom_layer_t *input_s(const nnom_io_config_t* config)
+{
+	nnom_io_layer_t *layer;
+	nnom_layer_io_t *in, *out;
+	// apply a block memory for all the sub handles.
+	layer = nnom_mem(sizeof(nnom_io_layer_t) + sizeof(nnom_layer_io_t) * 2);
+	if (layer == NULL)
+		return NULL;
+
+	// distribut the memory to sub handles.
+	in = (void *)((uint8_t*)layer + sizeof(nnom_io_layer_t));
+	out = (void *)((uint8_t*)in + sizeof(nnom_layer_io_t));
+
+	// set type in layer parent
+	layer->super.type = NNOM_INPUT;
+	layer->super.run = input_run;
+	layer->super.build = input_build;
+	// set buf state
+	in->type = NNOM_TENSOR_BUF_TEMP;
+	out->type = NNOM_TENSOR_BUF_NULL;
+	// put in & out on the layer.
+	layer->super.in = io_init(layer, in);
+	layer->super.out = io_init(layer, out);
+
+	/*
+	// some other layers (Conv, pooling) are not supporting 12 d input, we still expand the 1,2 dimension to 3
+    // test -> native support 1,2,3 D input. 
+	layer->super.in->tensor = new_tensor(NNOM_QTYPE_PER_TENSOR, config->tensor->num_dim, tensor_get_num_channel(config->tensor));
+	tensor_cpy_attr(layer->super.in->tensor, config->tensor);
+	layer->buf = config->tensor->p_data;
+	layer->dec_bit = config->tensor->q_dec[0];
+	*/
+
+	// set parameters
+    if(config->tensor->num_dim == 1) // test for 1d input, expend h = 1
+        layer->shape = shape(1, 1, config->tensor->dim[0]);
+    else if (config->tensor->num_dim == 2) // test for 1d input, expend h = 1
+		layer->shape = shape(1, config->tensor->dim[0], config->tensor->dim[1]);
+	else
+		layer->shape = shape(config->tensor->dim[0], config->tensor->dim[1], config->tensor->dim[2]);
+	layer->buf = config->tensor->p_data;
+	layer->dec_bit = config->tensor->q_dec[0];
+
+	// experimental: fixed input dim to 3
+	// input normally dont have a tensor, so we create one to store the initial data. 
+	nnom_shape_data_t dim[3] = {layer->shape.h, layer->shape.w, layer->shape.c};
+	layer->super.in->tensor = new_tensor(NNOM_QTYPE_PER_TENSOR, 3, tensor_get_num_channel(config->tensor));
+	tensor_set_attr_v(layer->super.in->tensor, layer->dec_bit, 0, dim, sizeof(dim)/sizeof(nnom_shape_data_t), 8);
+	return (nnom_layer_t *)layer;
+}
+
+nnom_layer_t *Input(nnom_3d_shape_t input_shape, void *p_buf)
+{
+	nnom_io_layer_t *layer;
+	nnom_layer_io_t *in, *out;
+
+	// apply a block memory for all the sub handles.
+	layer = nnom_mem(sizeof(nnom_io_layer_t) + sizeof(nnom_layer_io_t) * 2);
+	if (layer == NULL)
+		return NULL;
+
+	// distribut the memory to sub handles.
+	in = (void *)((uint8_t*)layer + sizeof(nnom_io_layer_t));
+	out = (void *)((uint8_t*)in + sizeof(nnom_layer_io_t));
+
+	// set type in layer parent
+	layer->super.type = NNOM_INPUT;
+	layer->super.run = input_run;
+	layer->super.build = input_build;
+	// set buf state
+	in->type = NNOM_TENSOR_BUF_TEMP;
+	out->type = NNOM_TENSOR_BUF_NULL;
+	// put in & out on the layer.
+	layer->super.in = io_init(layer, in);
+	layer->super.out = io_init(layer, out);
+
+	// set parameters
+	layer->shape = input_shape;
+	layer->buf = p_buf;
+	layer->dec_bit = 7;
+
+	// experimental: fixed input dim to 3
+	// input normally dont have a tensor, so we create one to store the initial data. 
+	nnom_shape_data_t dim[3] = { input_shape.h, input_shape.w, input_shape.c };
+	layer->super.in->tensor = new_tensor(NNOM_QTYPE_PER_TENSOR, 3, input_shape.c);
+	tensor_set_attr_v(layer->super.in->tensor, layer->dec_bit, 0, dim, sizeof(dim)/sizeof(nnom_shape_data_t), 8);
+	return (nnom_layer_t *)layer;
+}
+
+nnom_status_t input_build(nnom_layer_t* layer)
+{
+	// the input tensor of inputlayer has assigned previously 
+
+	// output tensor
+	// 1. allocate a new tensor for output
+	// 2. set the same dim, qfmt to the new tensor.
+	layer->out->tensor = new_tensor(NNOM_QTYPE_PER_TENSOR, layer->in->tensor->num_dim, tensor_get_num_channel(layer->in->tensor));
+	tensor_cpy_attr(layer->out->tensor, layer->in->tensor);
+
+	// now this build has passed the input tensors (shapes, formats) to the new tensors. 
+	return NN_SUCCESS;
+}
+
+
+nnom_status_t input_run(nnom_layer_t *layer)
+{
+	nnom_io_layer_t *cl = (nnom_io_layer_t *)layer;
+#ifdef NNOM_USING_CHW
+	if(layer->in->tensor->num_dim == 3)
+    {
+        nnom_3d_shape_t shape = {layer->in->tensor->dim[0], layer->in->tensor->dim[1], layer->in->tensor->dim[2]};
+        hwc2chw_q7(shape, cl->buf, layer->in->tensor->p_data);
+    }
+    else if (layer->in->tensor->num_dim == 2)
+    {
+        nnom_3d_shape_t shape = {1, layer->in->tensor->dim[0], layer->in->tensor->dim[1]};
+        hwc2chw_q7(shape, cl->buf, layer->in->tensor->p_data);
+    }
+    else
+#endif
+	nnom_memcpy(layer->in->tensor->p_data, cl->buf, tensor_size(layer->in->tensor));
+
+	return NN_SUCCESS;
+}