Coverage Report

Created: 2021-09-21 23:33

/home/liu/buildslave/linux-x64-runtests/build/test/unit/nnc/autograd.tests.c
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Source (jump to first uncovered line)
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#include "case.h"
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#include "ccv_case.h"
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#include "ccv_nnc_case.h"
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#include <ccv.h>
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#include <nnc/ccv_nnc.h>
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#include <nnc/ccv_nnc_easy.h>
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TEST_SETUP()
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{
10
  ccv_nnc_init();
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}
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TEST_CASE("simple autograd with D[x * x + Log[1 / x], x] when x = 0.84")
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{
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  ccv_nnc_symbolic_graph_t* symbolic_graph = ccv_nnc_symbolic_graph_new();
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  ccv_nnc_tensor_symbol_t one = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "1");
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  ccv_nnc_tensor_symbol_t x = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "x");
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  // w = x * x
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  ccv_nnc_tensor_symbol_t w = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "w");
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  // u = 1 / x
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1
  ccv_nnc_tensor_symbol_t u = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "u");
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1
  // v = Log[u]
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  ccv_nnc_tensor_symbol_t v = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "v");
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  // z = w + v
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  ccv_nnc_tensor_symbol_t z = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "z");
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1
  ccv_nnc_graph_exec_symbol_t prod = ccv_nnc_graph_exec_symbol_new(symbolic_graph, CMD_EWPROD_FORWARD(), TENSOR_SYMBOL_LIST(x, x), TENSOR_SYMBOL_LIST(w), "prod");
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1
  ccv_nnc_graph_exec_symbol_t inv = ccv_nnc_graph_exec_symbol_new(symbolic_graph, CMD_EWDIV_FORWARD(), TENSOR_SYMBOL_LIST(one, x), TENSOR_SYMBOL_LIST(u), "inv");
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1
  ccv_nnc_graph_exec_symbol_t log = ccv_nnc_graph_exec_symbol_new(symbolic_graph, CMD_EWLOG_FORWARD(), TENSOR_SYMBOL_LIST(u), TENSOR_SYMBOL_LIST(v), "log");
29
1
  ccv_nnc_graph_exec_symbol_t sum = ccv_nnc_graph_exec_symbol_new(symbolic_graph, CMD_EWSUM_FORWARD(), TENSOR_SYMBOL_LIST(w, v), TENSOR_SYMBOL_LIST(z), "sum");
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1
  ccv_nnc_graph_exec_symbol_autogen(symbolic_graph, GRAPH_EXEC_SYMBOL_LIST(prod, inv, log, sum), 0);
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  ccv_nnc_symbolic_graph_backward(symbolic_graph, TENSOR_SYMBOL_LIST(z), TENSOR_SYMBOL_LIST(x), GRAPH_EXEC_SYMBOL_LIST(prod, inv), GRAPH_EXEC_SYMBOL_LIST(sum));
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  ccv_nnc_graph_t* graph = 0;
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1
  ccv_nnc_tensor_arena_t* tensor_arena = 0;
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1
  ccv_nnc_graph_exec_arena_t* graph_exec_arena = 0;
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1
  ccv_nnc_tensor_symbol_t dx = ccv_nnc_tensor_symbol_for_backward(symbolic_graph, x);
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1
  ccv_nnc_graph_exec_symbol_t dxc = ccv_nnc_graph_exec_symbol_for_backward(symbolic_graph, dx);
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  ccv_nnc_symbolic_graph_compile(symbolic_graph, ccv_nnc_default_compile_params, 0, 0, 0, 0, GRAPH_EXEC_SYMBOL_LIST(prod, inv), GRAPH_EXEC_SYMBOL_LIST(dxc, sum), &graph, &tensor_arena, &graph_exec_arena);
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1
  SYMBOLIC_GRAPH_GEN(symbolic_graph, CCV_NNC_LONG_DOT_GRAPH);
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  GRAPH_GEN(graph, CCV_NNC_LONG_DOT_GRAPH);
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  ccv_nnc_tensor_t* tone = ccv_nnc_tensor_from_symbol(tensor_arena, one);
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1
  tone->data.f32[0] = 1;
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  ccv_nnc_tensor_t* tx = ccv_nnc_tensor_from_symbol(tensor_arena, x);
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  tx->data.f32[0] = 0.84;
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  ccv_nnc_tensor_symbol_t dz = ccv_nnc_tensor_symbol_for_backward(symbolic_graph, z);
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  ccv_nnc_tensor_t* tdz = ccv_nnc_tensor_from_symbol(tensor_arena, dz);
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  // Seed the initialization vector.
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  tdz->data.f32[0] = 1;
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  ccv_nnc_graph_run(graph, 0, GRAPH_EXEC_LIST(ccv_nnc_graph_exec_from_symbol(graph_exec_arena, prod), ccv_nnc_graph_exec_from_symbol(graph_exec_arena, inv)), GRAPH_EXEC_LIST(ccv_nnc_graph_exec_from_symbol(graph_exec_arena, dxc), ccv_nnc_graph_exec_from_symbol(graph_exec_arena, sum)), 0, 0);
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  ccv_nnc_tensor_t* tz = ccv_nnc_tensor_from_symbol(tensor_arena, z);
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  ccv_nnc_tensor_t* tdx = ccv_nnc_tensor_from_symbol(tensor_arena, dx);
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  REQUIRE_EQ_WITH_TOLERANCE(tz->data.f32[0], 0.84 * 0.84 + logf(1.0 / 0.84), 1e-6, "computed result of x * x + Log[1 / x] should be the same");
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  REQUIRE_EQ_WITH_TOLERANCE(tdx->data.f32[0], 2 * 0.84 - (1.0 / 0.84), 1e-6, "computed result of D[x * x + Log[1 / x], x] should be the same");
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  ccv_nnc_symbolic_graph_free(symbolic_graph);
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  ccv_nnc_graph_free(graph);
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  ccv_nnc_tensor_arena_free(tensor_arena);
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  ccv_nnc_graph_exec_arena_free(graph_exec_arena);
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}
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TEST_CASE("autograd with D[y, x] when x = 10 and y = 1 (no x presence in the formula)")
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{
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  ccv_nnc_symbolic_graph_t* symbolic_graph = ccv_nnc_symbolic_graph_new();
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  ccv_nnc_tensor_symbol_t x = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "x");
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  ccv_nnc_tensor_symbol_t y = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "y");
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  ccv_nnc_graph_exec_symbol_t set = ccv_nnc_graph_exec_symbol_new(symbolic_graph, CMD_SET_FORWARD(1), TENSOR_SYMBOL_LIST(), TENSOR_SYMBOL_LIST(y), "set");
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  ccv_nnc_graph_exec_symbol_autogen(symbolic_graph, 0, 0, CCV_NNC_AUTOGEN_ALL_EXECS | CCV_NNC_AUTOGEN_SOURCES_AND_DESTINATIONS);
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1
  ccv_nnc_symbolic_graph_backward(symbolic_graph, TENSOR_SYMBOL_LIST(y), TENSOR_SYMBOL_LIST(x), GRAPH_EXEC_SYMBOL_LIST(set), GRAPH_EXEC_SYMBOL_LIST(set));
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  SYMBOLIC_GRAPH_GEN(symbolic_graph, CCV_NNC_LONG_DOT_GRAPH);
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1
  ccv_nnc_graph_t* graph = 0;
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  ccv_nnc_tensor_arena_t* tensor_arena = 0;
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  ccv_nnc_graph_exec_arena_t* graph_exec_arena = 0;
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  ccv_nnc_tensor_symbol_t dx = ccv_nnc_tensor_symbol_for_backward(symbolic_graph, x);
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  ccv_nnc_graph_exec_symbol_autogen(symbolic_graph, 0, 0, CCV_NNC_AUTOGEN_SOURCES_AND_DESTINATIONS);
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  ccv_nnc_symbolic_graph_compile(symbolic_graph, ccv_nnc_default_compile_params, 0, 0, 0, 0, ccv_nnc_symbolic_graph_sources(symbolic_graph), ccv_nnc_symbolic_graph_source_size(symbolic_graph), ccv_nnc_symbolic_graph_destinations(symbolic_graph), ccv_nnc_symbolic_graph_destination_size(symbolic_graph), &graph, &tensor_arena, &graph_exec_arena);
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  GRAPH_GEN(graph, CCV_NNC_LONG_DOT_GRAPH);
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  ccv_nnc_tensor_t* tx = ccv_nnc_tensor_from_symbol(tensor_arena, x);
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1
  if (tx)
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0
    tx->data.f32[0] = 10;
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  ccv_nnc_tensor_t* ty = ccv_nnc_tensor_from_symbol(tensor_arena, y);
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1
  if (ty)
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    ty->data.f32[0] = 1;
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  ccv_nnc_tensor_symbol_t dy = ccv_nnc_tensor_symbol_for_backward(symbolic_graph, y);
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  ccv_nnc_tensor_t* tdy = ccv_nnc_tensor_from_symbol(tensor_arena, dy);
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  // Seed the initialization vector if needed.
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  if (tdy)
85
0
    tdy->data.f32[0] = 1;
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  ccv_nnc_graph_exec_t source = ccv_nnc_graph_exec_source(graph_exec_arena);
87
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  ccv_nnc_graph_exec_t destination = ccv_nnc_graph_exec_destination(graph_exec_arena);
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  ccv_nnc_graph_run(graph, 0, &source, 1, &destination, 1, 0, 0);
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  ccv_nnc_tensor_t* tdx = ccv_nnc_tensor_from_symbol(tensor_arena, dx);
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  REQUIRE_EQ_WITH_TOLERANCE(tdx->data.f32[0], 0, 1e-6, "computed result of D[y, x] should be 0");
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  ccv_nnc_symbolic_graph_free(symbolic_graph);
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  ccv_nnc_graph_free(graph);
93
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  ccv_nnc_tensor_arena_free(tensor_arena);
94
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  ccv_nnc_graph_exec_arena_free(graph_exec_arena);
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1
}
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TEST_CASE("autograd with D[(x - y) * (x + 1), [x, y]] when x = 43.24 and y = 0.38")
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{
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  ccv_nnc_symbolic_graph_t* symbolic_graph = ccv_nnc_symbolic_graph_new();
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  ccv_nnc_tensor_symbol_t one = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "1");
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  ccv_nnc_tensor_symbol_t x = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "x");
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  ccv_nnc_tensor_symbol_t y = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "y");
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  // w = x - y
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  ccv_nnc_tensor_symbol_t w = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "w");
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  // u = y + 1
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  ccv_nnc_tensor_symbol_t u = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "u");
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  // v = w * u
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  ccv_nnc_tensor_symbol_t v = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "v");
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  ccv_nnc_graph_exec_symbol_t minus = ccv_nnc_graph_exec_symbol_new(symbolic_graph, CMD_ADD_FORWARD(1, -1), TENSOR_SYMBOL_LIST(x, y), TENSOR_SYMBOL_LIST(w), "minus");
110
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  ccv_nnc_graph_exec_symbol_t plus = ccv_nnc_graph_exec_symbol_new(symbolic_graph, CMD_ADD_FORWARD(1, 1), TENSOR_SYMBOL_LIST(y, one), TENSOR_SYMBOL_LIST(u), "plus");
111
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  ccv_nnc_graph_exec_symbol_t prod = ccv_nnc_graph_exec_symbol_new(symbolic_graph, CMD_EWPROD_FORWARD(), TENSOR_SYMBOL_LIST(w, u), TENSOR_SYMBOL_LIST(v), "prod");
112
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  ccv_nnc_graph_exec_symbol_autogen(symbolic_graph, GRAPH_EXEC_SYMBOL_LIST(minus, plus, prod), 0);
113
1
  ccv_nnc_symbolic_graph_backward(symbolic_graph, TENSOR_SYMBOL_LIST(v), TENSOR_SYMBOL_LIST(x, y), GRAPH_EXEC_SYMBOL_LIST(minus, plus), GRAPH_EXEC_SYMBOL_LIST(prod));
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  ccv_nnc_graph_t* graph = 0;
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  ccv_nnc_tensor_arena_t* tensor_arena = 0;
116
1
  ccv_nnc_graph_exec_arena_t* graph_exec_arena = 0;
117
1
  ccv_nnc_tensor_symbol_t dx = ccv_nnc_tensor_symbol_for_backward(symbolic_graph, x);
118
1
  ccv_nnc_graph_exec_symbol_t dxc = ccv_nnc_graph_exec_symbol_for_backward(symbolic_graph, dx);
119
1
  ccv_nnc_tensor_symbol_t dy = ccv_nnc_tensor_symbol_for_backward(symbolic_graph, y);
120
1
  ccv_nnc_graph_exec_symbol_t dyc = ccv_nnc_graph_exec_symbol_for_backward(symbolic_graph, dy);
121
1
  ccv_nnc_symbolic_graph_compile(symbolic_graph, ccv_nnc_default_compile_params, 0, 0, 0, 0, GRAPH_EXEC_SYMBOL_LIST(minus, plus), GRAPH_EXEC_SYMBOL_LIST(dxc, dyc, prod), &graph, &tensor_arena, &graph_exec_arena);
122
1
  SYMBOLIC_GRAPH_GEN(symbolic_graph, CCV_NNC_LONG_DOT_GRAPH);
123
1
  GRAPH_GEN(graph, CCV_NNC_LONG_DOT_GRAPH);
124
1
  ccv_nnc_tensor_t* tone = ccv_nnc_tensor_from_symbol(tensor_arena, one);
125
1
  tone->data.f32[0] = 1;
126
1
  ccv_nnc_tensor_t* tx = ccv_nnc_tensor_from_symbol(tensor_arena, x);
127
1
  tx->data.f32[0] = 43.24;
128
1
  ccv_nnc_tensor_t* ty = ccv_nnc_tensor_from_symbol(tensor_arena, y);
129
1
  ty->data.f32[0] = 0.38;
130
1
  ccv_nnc_tensor_symbol_t dv = ccv_nnc_tensor_symbol_for_backward(symbolic_graph, v);
131
1
  ccv_nnc_tensor_t* tdv = ccv_nnc_tensor_from_symbol(tensor_arena, dv);
132
1
  // Seed the initialization vector.
133
1
  tdv->data.f32[0] = 1;
134
1
  ccv_nnc_graph_run(graph, 0, GRAPH_EXEC_LIST(ccv_nnc_graph_exec_from_symbol(graph_exec_arena, minus), ccv_nnc_graph_exec_from_symbol(graph_exec_arena, plus)), GRAPH_EXEC_LIST(ccv_nnc_graph_exec_from_symbol(graph_exec_arena, dxc), ccv_nnc_graph_exec_from_symbol(graph_exec_arena, dyc), ccv_nnc_graph_exec_from_symbol(graph_exec_arena, prod)), 0, 0);
135
1
  ccv_nnc_tensor_t* tv = ccv_nnc_tensor_from_symbol(tensor_arena, v);
136
1
  ccv_nnc_tensor_t* tdx = ccv_nnc_tensor_from_symbol(tensor_arena, dx);
137
1
  ccv_nnc_tensor_t* tdy = ccv_nnc_tensor_from_symbol(tensor_arena, dy);
138
1
  REQUIRE_EQ_WITH_TOLERANCE(tv->data.f32[0], (43.24 - 0.38) * (0.38 + 1), 1e-6, "computed result of (x + y) * (y + 1) should be the same");
139
1
  REQUIRE_EQ_WITH_TOLERANCE(tdx->data.f32[0], 0.38 + 1, 1e-6, "computed result of D[(x + y) * (y + 1), x] should be the same");
140
1
  REQUIRE_EQ_WITH_TOLERANCE(tdy->data.f32[0], -2 * 0.38 + 43.24 - 1, 1e-6, "computed result of D[(x + y) * (y + 1), y] should be the same");
141
1
  ccv_nnc_symbolic_graph_free(symbolic_graph);
142
1
  ccv_nnc_graph_free(graph);
143
1
  ccv_nnc_tensor_arena_free(tensor_arena);
144
1
  ccv_nnc_graph_exec_arena_free(graph_exec_arena);
145
1
}
146
147
TEST_CASE("partial autograd with D[y * x + Log[1 / x], y] when x = 0.84 and y = 1.23")
148
1
{
149
1
  ccv_nnc_symbolic_graph_t* symbolic_graph = ccv_nnc_symbolic_graph_new();
150
1
  ccv_nnc_tensor_symbol_t one = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "1");
151
1
  ccv_nnc_tensor_symbol_t x = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "x");
152
1
  ccv_nnc_tensor_symbol_t y = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "y");
153
1
  // w = y * x
154
1
  ccv_nnc_tensor_symbol_t w = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "w");
155
1
  // u = 1 / x
156
1
  ccv_nnc_tensor_symbol_t u = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "u");
157
1
  // v = Log[u]
158
1
  ccv_nnc_tensor_symbol_t v = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "v");
159
1
  // z = w + v
160
1
  ccv_nnc_tensor_symbol_t z = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "z");
161
1
  ccv_nnc_graph_exec_symbol_t prod = ccv_nnc_graph_exec_symbol_new(symbolic_graph, CMD_EWPROD_FORWARD(), TENSOR_SYMBOL_LIST(y, x), TENSOR_SYMBOL_LIST(w), "prod");
162
1
  ccv_nnc_graph_exec_symbol_t inv = ccv_nnc_graph_exec_symbol_new(symbolic_graph, CMD_EWDIV_FORWARD(), TENSOR_SYMBOL_LIST(one, x), TENSOR_SYMBOL_LIST(u), "inv");
163
1
  ccv_nnc_graph_exec_symbol_t log = ccv_nnc_graph_exec_symbol_new(symbolic_graph, CMD_EWLOG_FORWARD(), TENSOR_SYMBOL_LIST(u), TENSOR_SYMBOL_LIST(v), "log");
164
1
  ccv_nnc_graph_exec_symbol_t sum = ccv_nnc_graph_exec_symbol_new(symbolic_graph, CMD_EWSUM_FORWARD(), TENSOR_SYMBOL_LIST(w, v), TENSOR_SYMBOL_LIST(z), "sum");
165
1
  ccv_nnc_graph_exec_symbol_autogen(symbolic_graph, GRAPH_EXEC_SYMBOL_LIST(prod, inv, log, sum), 0);
166
1
  ccv_nnc_symbolic_graph_backward(symbolic_graph, TENSOR_SYMBOL_LIST(z), TENSOR_SYMBOL_LIST(y), GRAPH_EXEC_SYMBOL_LIST(prod, inv), GRAPH_EXEC_SYMBOL_LIST(sum));
167
1
  ccv_nnc_graph_t* graph = 0;
168
1
  ccv_nnc_tensor_arena_t* tensor_arena = 0;
169
1
  ccv_nnc_graph_exec_arena_t* graph_exec_arena = 0;
170
1
  ccv_nnc_tensor_symbol_t dy = ccv_nnc_tensor_symbol_for_backward(symbolic_graph, y);
171
1
  ccv_nnc_graph_exec_symbol_t dyc = ccv_nnc_graph_exec_symbol_for_backward(symbolic_graph, dy);
172
1
  ccv_nnc_symbolic_graph_compile(symbolic_graph, ccv_nnc_default_compile_params, 0, 0, 0, 0, GRAPH_EXEC_SYMBOL_LIST(prod, inv), GRAPH_EXEC_SYMBOL_LIST(dyc, sum), &graph, &tensor_arena, &graph_exec_arena);
173
1
  SYMBOLIC_GRAPH_GEN(symbolic_graph, CCV_NNC_LONG_DOT_GRAPH);
174
1
  ccv_nnc_graph_set_default_static_schedule(graph, CCV_STREAM_CONTEXT_CPU);
175
1
  GRAPH_GEN(graph, CCV_NNC_LONG_DOT_GRAPH);
176
1
  ccv_nnc_tensor_t* tone = ccv_nnc_tensor_from_symbol(tensor_arena, one);
177
1
  tone->data.f32[0] = 1;
178
1
  ccv_nnc_tensor_t* tx = ccv_nnc_tensor_from_symbol(tensor_arena, x);
179
1
  tx->data.f32[0] = 0.84;
180
1
  ccv_nnc_tensor_t* ty = ccv_nnc_tensor_from_symbol(tensor_arena, y);
181
1
  ty->data.f32[0] = 1.23;
182
1
  ccv_nnc_tensor_symbol_t dz = ccv_nnc_tensor_symbol_for_backward(symbolic_graph, z);
183
1
  ccv_nnc_tensor_t* tdz = ccv_nnc_tensor_from_symbol(tensor_arena, dz);
184
1
  // Seed the initialization vector.
185
1
  tdz->data.f32[0] = 1;
186
1
  ccv_nnc_graph_run(graph, 0, GRAPH_EXEC_LIST(ccv_nnc_graph_exec_from_symbol(graph_exec_arena, prod), ccv_nnc_graph_exec_from_symbol(graph_exec_arena, inv)), GRAPH_EXEC_LIST(ccv_nnc_graph_exec_from_symbol(graph_exec_arena, dyc), ccv_nnc_graph_exec_from_symbol(graph_exec_arena, sum)), 0, 0);
187
1
  ccv_nnc_tensor_t* tz = ccv_nnc_tensor_from_symbol(tensor_arena, z);
188
1
  ccv_nnc_tensor_t* tdy = ccv_nnc_tensor_from_symbol(tensor_arena, dy);
189
1
  REQUIRE_EQ_WITH_TOLERANCE(tz->data.f32[0], 1.23 * 0.84 + logf(1.0 / 0.84), 1e-6, "computed result of y * x + Log[1 / x] should be the same");
190
1
  REQUIRE_EQ_WITH_TOLERANCE(tdy->data.f32[0], 0.84, 1e-6, "computed result of D[y * x + Log[1 / x], y] should be the same");
191
1
  ccv_nnc_symbolic_graph_free(symbolic_graph);
192
1
  ccv_nnc_graph_free(graph);
193
1
  ccv_nnc_tensor_arena_free(tensor_arena);
194
1
  ccv_nnc_graph_exec_arena_free(graph_exec_arena);
195
1
}
196
197
TEST_CASE("autograd with D[x * x + Log[1 / x], x] D[y * y + Log[1 / y], y] when x = 0.84 and y = 0.24")
198
1
{
199
1
  ccv_nnc_symbolic_graph_t* symbolic_graph = ccv_nnc_symbolic_graph_new();
200
1
  ccv_nnc_tensor_symbol_t one = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "1");
201
1
  ccv_nnc_tensor_symbol_t x0 = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "x");
202
1
  // w = x * x
203
1
  ccv_nnc_tensor_symbol_t w0 = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "w");
204
1
  // u = 1 / x
205
1
  ccv_nnc_tensor_symbol_t u0 = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "u");
206
1
  // v = Log[u]
207
1
  ccv_nnc_tensor_symbol_t v0 = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "v");
208
1
  // z = w + v
209
1
  ccv_nnc_tensor_symbol_t z0 = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "z");
210
1
  ccv_nnc_graph_exec_symbol_new(symbolic_graph, CMD_EWPROD_FORWARD(), TENSOR_SYMBOL_LIST(x0, x0), TENSOR_SYMBOL_LIST(w0), "prod0");
211
1
  ccv_nnc_graph_exec_symbol_new(symbolic_graph, CMD_EWDIV_FORWARD(), TENSOR_SYMBOL_LIST(one, x0), TENSOR_SYMBOL_LIST(u0), "inv0");
212
1
  ccv_nnc_graph_exec_symbol_new(symbolic_graph, CMD_EWLOG_FORWARD(), TENSOR_SYMBOL_LIST(u0), TENSOR_SYMBOL_LIST(v0), "log0");
213
1
  ccv_nnc_graph_exec_symbol_new(symbolic_graph, CMD_EWSUM_FORWARD(), TENSOR_SYMBOL_LIST(w0, v0), TENSOR_SYMBOL_LIST(z0), "sum0");
214
1
  ccv_nnc_tensor_symbol_t x1 = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "x");
215
1
  // w = x * x
216
1
  ccv_nnc_tensor_symbol_t w1 = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "w");
217
1
  // u = 1 / x
218
1
  ccv_nnc_tensor_symbol_t u1 = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "u");
219
1
  // v = Log[u]
220
1
  ccv_nnc_tensor_symbol_t v1 = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "v");
221
1
  // z = w + v
222
1
  ccv_nnc_tensor_symbol_t z1 = ccv_nnc_tensor_symbol_new(symbolic_graph, CPU_TENSOR_NHWC(32F, 1), "z");
223
1
  ccv_nnc_graph_exec_symbol_new(symbolic_graph, CMD_EWPROD_FORWARD(), TENSOR_SYMBOL_LIST(x1, x1), TENSOR_SYMBOL_LIST(w1), "prod1");
224
1
  ccv_nnc_graph_exec_symbol_new(symbolic_graph, CMD_EWDIV_FORWARD(), TENSOR_SYMBOL_LIST(one, x1), TENSOR_SYMBOL_LIST(u1), "inv1");
225
1
  ccv_nnc_graph_exec_symbol_new(symbolic_graph, CMD_EWLOG_FORWARD(), TENSOR_SYMBOL_LIST(u1), TENSOR_SYMBOL_LIST(v1), "log1");
226
1
  ccv_nnc_graph_exec_symbol_new(symbolic_graph, CMD_EWSUM_FORWARD(), TENSOR_SYMBOL_LIST(w1, v1), TENSOR_SYMBOL_LIST(z1), "sum1");
227
1
  ccv_nnc_graph_exec_symbol_autogen(symbolic_graph, 0, 0, CCV_NNC_AUTOGEN_ALL_EXECS | CCV_NNC_AUTOGEN_SOURCES_AND_DESTINATIONS);
228
1
  ccv_nnc_symbolic_graph_backward(symbolic_graph, TENSOR_SYMBOL_LIST(z0, z1), TENSOR_SYMBOL_LIST(x0, x1), SYMBOLIC_GRAPH_SOURCES(symbolic_graph), SYMBOLIC_GRAPH_DESTINATIONS(symbolic_graph));
229
1
  ccv_nnc_graph_exec_symbol_autogen(symbolic_graph, 0, 0, CCV_NNC_AUTOGEN_ALL_EXECS | CCV_NNC_AUTOGEN_SOURCES_AND_DESTINATIONS);
230
1
  SYMBOLIC_GRAPH_GEN(symbolic_graph, CCV_NNC_LONG_DOT_GRAPH);
231
1
  ccv_nnc_graph_t* graph = 0;
232
1
  ccv_nnc_tensor_arena_t* tensor_arena = 0;
233
1
  ccv_nnc_graph_exec_arena_t* graph_exec_arena = 0;
234
1
  ccv_nnc_tensor_symbol_t dx0 = ccv_nnc_tensor_symbol_for_backward(symbolic_graph, x0);
235
1
  ccv_nnc_tensor_symbol_t dx1 = ccv_nnc_tensor_symbol_for_backward(symbolic_graph, x1);
236
1
  ccv_nnc_symbolic_graph_compile(symbolic_graph, ccv_nnc_default_compile_params,
237
1
    0, 0,
238
1
    TENSOR_SYMBOL_LIST(z0, z1),
239
1
    SYMBOLIC_GRAPH_SOURCES(symbolic_graph), SYMBOLIC_GRAPH_DESTINATIONS(symbolic_graph),
240
1
    &graph, &tensor_arena, &graph_exec_arena);
241
1
  GRAPH_GEN(graph, CCV_NNC_LONG_DOT_GRAPH);
242
1
  ccv_nnc_tensor_t* tone = ccv_nnc_tensor_from_symbol(tensor_arena, one);
243
1
  tone->data.f32[0] = 1;
244
1
  ccv_nnc_tensor_t* tx0 = ccv_nnc_tensor_from_symbol(tensor_arena, x0);
245
1
  tx0->data.f32[0] = 0.84;
246
1
  ccv_nnc_tensor_t* tx1 = ccv_nnc_tensor_from_symbol(tensor_arena, x1);
247
1
  tx1->data.f32[0] = 0.24;
248
1
  ccv_nnc_tensor_symbol_t dz0 = ccv_nnc_tensor_symbol_for_backward(symbolic_graph, z0);
249
1
  ccv_nnc_tensor_t* tdz0 = ccv_nnc_tensor_from_symbol(tensor_arena, dz0);
250
1
  ccv_nnc_tensor_symbol_t dz1 = ccv_nnc_tensor_symbol_for_backward(symbolic_graph, z1);
251
1
  ccv_nnc_tensor_t* tdz1 = ccv_nnc_tensor_from_symbol(tensor_arena, dz1);
252
1
  // Seed the initialization vector.
253
1
  tdz0->data.f32[0] = 1;
254
1
  tdz1->data.f32[0] = 1;
255
1
  ccv_nnc_graph_run(graph, 0, TRAVERSE_FULL, 0, 0);
256
1
  ccv_nnc_tensor_t* tz0 = ccv_nnc_tensor_from_symbol(tensor_arena, z0);
257
1
  ccv_nnc_tensor_t* tdx0 = ccv_nnc_tensor_from_symbol(tensor_arena, dx0);
258
1
  ccv_nnc_tensor_t* tz1 = ccv_nnc_tensor_from_symbol(tensor_arena, z1);
259
1
  ccv_nnc_tensor_t* tdx1 = ccv_nnc_tensor_from_symbol(tensor_arena, dx1);
260
1
  REQUIRE_EQ_WITH_TOLERANCE(tz0->data.f32[0], 0.84 * 0.84 + logf(1.0 / 0.84), 1e-6, "computed result of x * x + Log[1 / x] should be the same");
261
1
  REQUIRE_EQ_WITH_TOLERANCE(tdx0->data.f32[0], 2 * 0.84 - (1.0 / 0.84), 1e-6, "computed result of D[x * x + Log[1 / x], x] should be the same");
262
1
  REQUIRE_EQ_WITH_TOLERANCE(tz1->data.f32[0], 0.24 * 0.24 + logf(1.0 / 0.24), 1e-6, "computed result of y * y + Log[1 / y] should be the same");
263
1
  REQUIRE_EQ_WITH_TOLERANCE(tdx1->data.f32[0], 2 * 0.24 - (1.0 / 0.24), 1e-6, "computed result of D[y * y + Log[1 / y], y] should be the same");
264
1
  ccv_nnc_symbolic_graph_free(symbolic_graph);
265
1
  ccv_nnc_graph_free(graph);
266
1
  ccv_nnc_tensor_arena_free(tensor_arena);
267
1
  ccv_nnc_graph_exec_arena_free(graph_exec_arena);
268
1
}
269
270
#include "case_main.h"