Enable cppcheck rule for 'not', 'or' keywords (#1361)

Using not and or improves readability. The cppcheck rule will help ensure we are doing it consistently.

src/rewrite_pooling.cpp

@@ -47,12 +47,12 @@ void rewrite_pooling::apply(module& m) const
         if(not s.standard())
             continue;
         auto&& op = any_cast<op::pooling>(ins->get_operator());
-        if(!std::all_of(op.padding.begin(), op.padding.end(), [](auto i) { return i == 0; }))
+        if(not std::all_of(op.padding.begin(), op.padding.end(), [](auto i) { return i == 0; }))
             continue;
-        if(!std::all_of(op.stride.begin(), op.stride.end(), [](auto i) { return i == 1; }))
+        if(not std::all_of(op.stride.begin(), op.stride.end(), [](auto i) { return i == 1; }))
             continue;
         auto lens = s.lens();
-        if(!std::equal(lens.begin() + 2, lens.end(), op.lengths.begin(), op.lengths.end()))
+        if(not std::equal(lens.begin() + 2, lens.end(), op.lengths.begin(), op.lengths.end()))
             continue;
         std::int64_t n = s.lens()[0];
         std::int64_t c = s.lens()[1];

src/rewrite_rnn.cpp

@@ -214,7 +214,7 @@ void rewrite_rnn::apply_vanilla_rnn(module& m, instruction_ref ins) const
             ih = m.add_literal(migraphx::literal{ih_shape, data});
         }
 
-        if(!is_forward and variable_seq_len)
+        if(not is_forward and variable_seq_len)
         {
             args[0] =
                 m.insert_instruction(ins, make_op("rnn_var_sl_shift_sequence"), args[0], seq_lens);
@@ -520,7 +520,7 @@ void rewrite_rnn::apply_gru(module& m, instruction_ref ins) const
             ih = m.add_literal(migraphx::literal{ih_shape, data});
         }
 
-        if(!is_forward and variable_seq_len)
+        if(not is_forward and variable_seq_len)
         {
             args[0] =
                 m.insert_instruction(ins, make_op("rnn_var_sl_shift_sequence"), args[0], seq_lens);
@@ -977,7 +977,7 @@ void rewrite_rnn::apply_lstm(module& m, instruction_ref ins) const
             pph = args[7];
         }
 
-        if(!is_forward and variable_seq_len)
+        if(not is_forward and variable_seq_len)
         {
             args[0] =
                 m.insert_instruction(ins, make_op("rnn_var_sl_shift_sequence"), args[0], seq_lens);
@@ -1294,11 +1294,11 @@ bool rewrite_rnn::is_variable_seq_lens(const module& m, instruction_ref seq_lens
             std::vector<int64_t> vec_lens;
             arg_lens.visit([&](auto l) { vec_lens.assign(l.begin(), l.end()); });
             int64_t l = 0;
-            if(!vec_lens.empty())
+            if(not vec_lens.empty())
             {
                 l = vec_lens[0];
             }
-            if(!std::all_of(vec_lens.begin(), vec_lens.end(), [&](auto v) { return v == l; }))
+            if(not std::all_of(vec_lens.begin(), vec_lens.end(), [&](auto v) { return v == l; }))
             {
                 is_var_lens = true;
             }
@@ -1318,7 +1318,7 @@ rewrite_rnn::get_seq_len(const module& m, instruction_ref input, instruction_ref
     bool is_var_lens = is_variable_seq_lens(m, seq_lens);
     auto input_shape = input->get_shape();
     auto length      = input_shape.lens()[0];
-    if(!is_var_lens and seq_lens != m.end())
+    if(not is_var_lens and seq_lens != m.end())
     {
         auto arg_len = seq_lens->eval();
         std::vector<std::size_t> vec_lens;
@@ -1387,7 +1387,7 @@ void rewrite_rnn::replace_last_cell_output(module& m,
 
     if(variable_seq_len)
     {
-        if(!ins_outputs.empty())
+        if(not ins_outputs.empty())
         {
             cell_outputs = m.insert_instruction(
                 std::next(ins),

src/shape.cpp

@@ -477,7 +477,7 @@ bool operator==(const shape::dynamic_dimension& x, const shape::dynamic_dimensio
 
 bool operator!=(const shape::dynamic_dimension& x, const shape::dynamic_dimension& y)
 {
-    return !(x == y);
+    return not(x == y);
 }
 std::ostream& operator<<(std::ostream& os, const shape::dynamic_dimension& x)
 {
@@ -497,7 +497,7 @@ bool operator==(const shape& x, const shape& y)
             x.strides() == y.strides() and x.sub_shapes() == y.sub_shapes());
 }
 
-bool operator!=(const shape& x, const shape& y) { return !(x == y); }
+bool operator!=(const shape& x, const shape& y) { return not(x == y); }
 
 std::ostream& operator<<(std::ostream& os, const shape& x)
 {

src/simplify_algebra.cpp

@@ -787,7 +787,7 @@ MIGRAPHX_PRED_MATCHER(horiz_conv_dot, instruction_ref ins)
     };
     auto dots  = std::count_if(ins->outputs().begin(), ins->outputs().end(), pred("dot"));
     auto convs = std::count_if(ins->outputs().begin(), ins->outputs().end(), pred("convolution"));
-    return !(dots < 2 and convs < 2);
+    return not(dots < 2 and convs < 2);
 }
 
 struct find_conv_dot_horiz_fusion
@@ -969,7 +969,7 @@ struct find_split_reshape
 
         // all outputs are reshape and of the same shape
         auto dims = any_cast<op::reshape>(rsp->get_operator()).dims;
-        if(!same_ops(vec_rsp))
+        if(not same_ops(vec_rsp))
         {
             return;
         }
@@ -1052,7 +1052,7 @@ struct find_split_transpose
 
         // all transpose are the same
         auto perm = any_cast<op::transpose>(trans->get_operator()).dims;
-        if(!same_ops(vec_trans))
+        if(not same_ops(vec_trans))
         {
             return;
         }

src/simplify_reshapes.cpp

@@ -99,7 +99,7 @@ struct find_reshaper
         std::vector<instruction_ref> reshapes{ins};
         while(is_reshaper(reshapes.back()))
         {
-            assert(!reshapes.back()->inputs().empty());
+            assert(not reshapes.back()->inputs().empty());
             assert(m.has_instruction(reshapes.back()->inputs().front()));
             auto input = reshapes.back()->inputs().front();
             reshapes.push_back(input);
@@ -288,7 +288,7 @@ struct find_concat_transpose
         auto permutation = find_permutation(s);
 
         // permutation should be the same for all inputs
-        if(!std::all_of(trans_inputs.begin(), trans_inputs.end(), [&](auto in) {
+        if(not std::all_of(trans_inputs.begin(), trans_inputs.end(), [&](auto in) {
                return (find_permutation(in->get_shape()) == permutation);
            }))
         {

src/targets/cpu/binary.cpp

@@ -49,7 +49,7 @@ struct dnnl_binary : dnnl_op<dnnl_binary, dnnl::binary>
         auto s0 = inputs.at(0);
         auto s1 = inputs.at(1);
         auto r  = s0;
-        if(s0 != s1 or !s0.packed())
+        if(s0 != s1 or not s0.packed())
         {
             r = shape{s0.type(), s0.lens()};
         }

src/targets/fpga/subgraph.cpp

@@ -95,7 +95,7 @@ void subgraph::apply(module_pass_manager& mpm) const
     for(auto it : iterator_for(mod))
     {
         // assuming we want all the params/literals as inputs to the FPGA submodule
-        if(migraphx::starts_with(it->name(), "@param") ||
+        if(migraphx::starts_with(it->name(), "@param") or
            migraphx::starts_with(it->name(), "@literal"))
         {
             literal_inputs.push_back(it);

src/targets/gpu/device/include/migraphx/gpu/device/array.hpp

@@ -131,7 +131,7 @@ struct hip_array
 
     friend MIGRAPHX_DEVICE_CONSTEXPR bool operator!=(const hip_array& x, const hip_array& y)
     {
-        return !(x == y);
+        return not(x == y);
     }
     // This uses the product order rather than lexical order
     friend MIGRAPHX_DEVICE_CONSTEXPR bool operator<(const hip_array& x, const hip_array& y)

src/targets/gpu/device/include/migraphx/gpu/device/visit.hpp

@@ -117,12 +117,13 @@ template <class V, class F, class... Ts>
 void hip_visit_all_impl(const shape& s, F f, V&& v, Ts&&... xs)
 {
     std::initializer_list<migraphx::shape::type_t> types = {get_shape(xs).type()...};
-    if(!std::all_of(
+    if(not std::all_of(
            types.begin(), types.end(), [&](migraphx::shape::type_t t) { return t == s.type(); }))
         MIGRAPHX_THROW("Types must be the same");
     std::initializer_list<index_int> ranks = {
         static_cast<index_int>(get_shape(xs).lens().size())...};
-    if(!std::all_of(ranks.begin(), ranks.end(), [&](index_int r) { return r == s.lens().size(); }))
+    if(not std::all_of(
+           ranks.begin(), ranks.end(), [&](index_int r) { return r == s.lens().size(); }))
         MIGRAPHX_THROW("Ranks must be the same");
     visit_tensor_size(s.lens().size(), [&](auto ndim) {
         s.visit_type(hip_visitor([&](auto as) { v(f(xs, ndim, as)...); }));
@@ -134,7 +135,8 @@ void hip_visit_views_impl(const shape& s, F f, V&& v, Ts&&... xs)
 {
     std::initializer_list<index_int> ranks = {
         static_cast<index_int>(get_shape(xs).lens().size())...};
-    if(!std::all_of(ranks.begin(), ranks.end(), [&](index_int r) { return r == s.lens().size(); }))
+    if(not std::all_of(
+           ranks.begin(), ranks.end(), [&](index_int r) { return r == s.lens().size(); }))
         MIGRAPHX_THROW("Ranks must be the same");
     visit_tensor_size(s.lens().size(), [&](auto ndim) { v(f(xs, ndim)...); });
 }

src/targets/gpu/device/multinomial.cpp

@@ -47,7 +47,7 @@ constexpr Iterator upper_bound(Iterator first, Iterator last, const T& value)
         it   = first;
         step = count / 2;
         std::advance(it, step);
-        if(!(value < *it))
+        if(not(value < *it))
         {
             first = ++it;
             count -= step + 1;

src/targets/gpu/gemm_impl.cpp

@@ -112,7 +112,7 @@ void gemm_impl(context& ctx,
                bool compute_fp32)
 {
     const bool is_3inputs = (args.size() == 4);
-    if(!is_3inputs)
+    if(not is_3inputs)
     {
         beta = 0;
     }

src/targets/gpu/kernels/include/migraphx/kernels/algorithm.hpp

@@ -163,7 +163,7 @@ constexpr Iterator1 search(Iterator1 first, Iterator1 last, Iterator2 s_first, I
             {
                 return last;
             }
-            if(!(*it == *s_it))
+            if(not(*it == *s_it))
             {
                 break;
             }

src/targets/gpu/kernels/include/migraphx/kernels/array.hpp

@@ -153,7 +153,7 @@ struct array
         return true;
     }
 
-    friend constexpr bool operator!=(const array& x, const array& y) { return !(x == y); }
+    friend constexpr bool operator!=(const array& x, const array& y) { return not(x == y); }
     // This uses the product order rather than lexical order
     friend constexpr bool operator<(const array& x, const array& y)
     {

src/targets/gpu/kernels/include/migraphx/kernels/integral_constant.hpp

@@ -73,10 +73,10 @@ MIGRAPHX_INTEGRAL_CONSTANT_BINARY_OP(!=)
 MIGRAPHX_INTEGRAL_CONSTANT_BINARY_OP(&)
 MIGRAPHX_INTEGRAL_CONSTANT_BINARY_OP(^)
 MIGRAPHX_INTEGRAL_CONSTANT_BINARY_OP(|)
-MIGRAPHX_INTEGRAL_CONSTANT_BINARY_OP(&&)
-MIGRAPHX_INTEGRAL_CONSTANT_BINARY_OP(||)
+MIGRAPHX_INTEGRAL_CONSTANT_BINARY_OP(and)
+MIGRAPHX_INTEGRAL_CONSTANT_BINARY_OP(or)
 
-MIGRAPHX_INTEGRAL_CONSTANT_UNARY_OP(!)
+MIGRAPHX_INTEGRAL_CONSTANT_UNARY_OP(not )
 MIGRAPHX_INTEGRAL_CONSTANT_UNARY_OP(~)
 MIGRAPHX_INTEGRAL_CONSTANT_UNARY_OP(+)
 MIGRAPHX_INTEGRAL_CONSTANT_UNARY_OP(-)

src/targets/gpu/lowering.cpp

@@ -341,7 +341,7 @@ struct miopen_apply
             catch(migraphx::exception&)
             {
                 // In case no solver supports the default format, retry using the other format.
-                compile_quant_conv_with_format(!int8_x4_format);
+                compile_quant_conv_with_format(not int8_x4_format);
             }
 
             auto args      = ins->inputs();

src/targets/gpu/mlir.cpp

@@ -78,7 +78,7 @@ struct mlir_handle
 
         friend bool operator==(ptr x, ptr y) { return x.get_value() == y.get_value(); }
 
-        friend bool operator!=(ptr x, ptr y) { return !(x == y); }
+        friend bool operator!=(ptr x, ptr y) { return not(x == y); }
         T obj{};
     };
 
@@ -503,7 +503,7 @@ struct mlir_program
                 pp =
                     problem_params{ins->get_operator(), to_shapes(ins->inputs()), ins->get_shape()};
                 std::string tuned = get_tune_params();
-                if(!tuned.empty())
+                if(not tuned.empty())
                     ops.add_attributes({{"perf_config", tuned}});
                 // check if HW supports xdlops
                 if(contains(get_xdlops_archs(), target_name))

src/targets/gpu/pack_int8_args.cpp

@@ -154,7 +154,7 @@ void pack_int8_args::apply(module& m) const
 
             bool transa = inputs[0]->get_shape().transposed();
             bool transb = inputs[1]->get_shape().transposed();
-            if(!transb)
+            if(not transb)
             {
                 auto packed_b = m.insert_instruction(
                     ins, make_op("hip::allocate", {{"shape", to_value(inputs[1]->get_shape())}}));

src/tf/parse_conv.cpp

@@ -100,7 +100,7 @@ struct parse_conv : op_parser<parse_conv>
                 {
                     MIGRAPHX_THROW("padding should have 4 values");
                 }
-                if(padding[0] != padding[2] || padding[1] != padding[3])
+                if(padding[0] != padding[2] or padding[1] != padding[3])
                 {
                     MIGRAPHX_THROW("migraphx does not support asymetric padding");
                 }

src/tf/parse_depthwiseconv.cpp

@@ -90,7 +90,7 @@ struct parse_depthwiseconv : op_parser<parse_depthwiseconv>
                 calculate_padding(0, pads, input_dims[2], op.stride[0], op.dilation[0], weight_h);
                 calculate_padding(1, pads, input_dims[3], op.stride[1], op.dilation[1], weight_w);
 
-                if(pads[0] != pads[2] || pads[1] != pads[3])
+                if(pads[0] != pads[2] or pads[1] != pads[3])
                 {
                     std::vector<int64_t> padding = {0, 0, pads[0], pads[1], 0, 0, pads[2], pads[3]};
                     l0 = info.add_instruction(migraphx::make_op("pad", {{"pads", padding}}), l0);

src/tf/parse_pooling.cpp

@@ -42,7 +42,7 @@ struct parse_pooling : op_parser<parse_pooling>
                           tf_parser::node_info info,
                           std::vector<instruction_ref> args) const
     {
-        if(!starts_with(opd.tf_name, "Max") && !starts_with(opd.tf_name, "Av"))
+        if(not starts_with(opd.tf_name, "Max") and not starts_with(opd.tf_name, "Av"))
         {
             MIGRAPHX_THROW("tf pooling mode must be Max or Average");
         }